A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 1 Input 0 called attribute0 range: 394 to 399 Input 1 called attribute1 range: 43 to 44.2 Input 2 called attribute2 range: 352 to 357 Input 3 called attribute3 range: 0 to 1.2 Input 4 called attribute4 range: 48.8 to 50 Output 0 called output0 range: 57.4 to 58.6 Output 1 called output1 range: 5640 to 5700 Output 2 called output2 range: 0.2 to 1.4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 **************************************************************** * * 1 points. Chose rsnum -1 (thus using 1 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 282.318 19.8323 16.183 0.632247 20.6292 * experiment 309.185 4.66456 357.179 0.970989 10.1891 * est rs center 293.286 25.7942 310.561 0.538521 24.9108 * est rs spread 59.4339 14.3333 172.27 0.268388 12.8639 * * ------------------------------ * att0: (399.601567-201.378202)/200.000000 = 0.991117 * att1: (49.886588-1.031188)/49.000000 = 0.997049 * att2: (592.743988-5.394077)/600.000000 = 0.978917 * att3: (0.993648-0.014206)/0.995000 = 0.984364 * att4: (48.877389-2.658505)/50.000000 = 0.924378 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 2 Input 0 called attribute0 range: 300 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 352 to 358 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 10 to 50 Output 0 called output0 range: 48 to 58 Output 1 called output1 range: 3500 to 6000 Output 2 called output2 range: 0.2 to 1.2 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 **************************************************************** * * 2 points. Chose rsnum -1 (thus using 2 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 387.175 1 600 1 0 * experiment 209.972 37.1164 18.6024 0.761891 37.8684 * est rs center 299.345 27.9771 314.184 0.456378 26.9143 * est rs spread 55.7466 13.4876 172.669 0.29834 14.1833 * * ------------------------------ * att0: (399.963444-202.830326)/200.000000 = 0.985666 * att1: (49.304429-1.486695)/49.000000 = 0.975872 * att2: (589.796503-3.831089)/600.000000 = 0.976609 * att3: (0.996903-0.007725)/0.995000 = 0.994148 * att4: (49.927591-0.723326)/50.000000 = 0.984085 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 3 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 400 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 10 to 50 Output 0 called output0 range: 48 to 58 Output 1 called output1 range: 2000 to 6000 Output 2 called output2 range: 0.2 to 1.2 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 **************************************************************** * * 3 points. Chose rsnum -1 (thus using 3 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 400 1 600 1 0 * experiment 390.006 24.478 204.662 0.131631 12.7733 * est rs center 299.355 26.3751 323.88 0.49281 25.9777 * est rs spread 63.3176 14.0152 176.816 0.296831 15.2656 * * ------------------------------ * att0: (399.513952-204.716600)/200.000000 = 0.973987 * att1: (49.711402-1.103341)/49.000000 = 0.992001 * att2: (596.748699-1.329154)/600.000000 = 0.992366 * att3: (0.997930-0.006067)/0.995000 = 0.996847 * att4: (49.872585-0.152265)/50.000000 = 0.994406 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 4 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 400 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 10 to 50 Output 0 called output0 range: 40 to 80 Output 1 called output1 range: 2000 to 10000 Output 2 called output2 range: 0.2 to 1.2 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 **************************************************************** * * 4 points. Chose rsnum -1 (thus using 4 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 1 0 1 0 * experiment 394.281 48.6348 82.6644 0.939786 24.2781 * est rs center 303.072 26.2448 291.998 0.490689 24.3922 * est rs spread 59.2442 13.8847 179.994 0.28564 14.2043 * * ------------------------------ * att0: (399.607343-201.057217)/200.000000 = 0.992751 * att1: (49.056604-1.699960)/49.000000 = 0.966462 * att2: (599.293770-0.939730)/600.000000 = 0.997257 * att3: (0.986793-0.015182)/0.995000 = 0.976494 * att4: (49.366636-0.667572)/50.000000 = 0.973981 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 5 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 400 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 10 to 50 Output 0 called output0 range: 40 to 120 Output 1 called output1 range: 2000 to 14000 Output 2 called output2 range: 0.2 to 1.2 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 **************************************************************** * * 5 points. Chose rsnum -1 (thus using 5 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 1 0 1 0 * experiment 251.91 6.21813 101.536 0.0850713 40.3065 * est rs center 298.325 25.3133 319.646 0.499777 24.7622 * est rs spread 54.8102 14.2601 164.91 0.299365 15.0298 * * ------------------------------ * att0: (399.047558-204.393958)/200.000000 = 0.973268 * att1: (49.335253-1.276435)/49.000000 = 0.980792 * att2: (594.516824-10.334904)/600.000000 = 0.973637 * att3: (0.994662-0.008511)/0.995000 = 0.991107 * att4: (49.773201-0.434831)/50.000000 = 0.986767 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 6 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 400 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 10 to 50 Output 0 called output0 range: 40 to 120 Output 1 called output1 range: 2000 to 14000 Output 2 called output2 range: 0.2 to 1.2 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 **************************************************************** * * 6 points. Chose rsnum -1 (thus using 6 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 1 0 1 0 * experiment 393.149 3.33586 549.51 0.492866 43.0287 * est rs center 305.306 26.6379 314.64 0.477613 25.9995 * est rs spread 57.3163 13.8262 170.694 0.316721 14.6755 * * ------------------------------ * att0: (399.496878-202.622100)/200.000000 = 0.984374 * att1: (49.283669-1.404736)/49.000000 = 0.977121 * att2: (598.623460-11.629208)/600.000000 = 0.978324 * att3: (0.986364-0.005961)/0.995000 = 0.985329 * att4: (49.459735-0.302735)/50.000000 = 0.983140 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 7 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 10 to 50 Output 0 called output0 range: 40 to 120 Output 1 called output1 range: 2000 to 14000 Output 2 called output2 range: 0.2 to 1.2 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 **************************************************************** * * 7 points. Chose rsnum -1 (thus using 7 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 1 0 1 0 * experiment 210.779 27.0031 557.61 0.6679 41.0007 * est rs center 304.107 25.6416 310.749 0.51368 24.0441 * est rs spread 54.982 14.9727 167.46 0.296597 14.8669 * * ------------------------------ * att0: (396.496047-201.366717)/200.000000 = 0.975647 * att1: (49.627991-1.009703)/49.000000 = 0.992210 * att2: (596.683466-4.306578)/600.000000 = 0.987295 * att3: (0.991819-0.021187)/0.995000 = 0.975509 * att4: (49.829929-1.173751)/50.000000 = 0.973124 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 8 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 10 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 14000 Output 2 called output2 range: 0 to 2 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 **************************************************************** * * 8 points. Chose rsnum -1 (thus using 8 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 30.151 600 1 50 * experiment 325.263 21.1426 219.813 0.735229 45.5875 * est rs center 300.13 25.8694 261.675 0.511957 26.4331 * est rs spread 56.3844 13.512 170.933 0.263078 14.1793 * * ------------------------------ * att0: (395.459560-205.253405)/200.000000 = 0.951031 * att1: (49.756957-1.846479)/49.000000 = 0.977765 * att2: (561.486047-0.440736)/600.000000 = 0.935076 * att3: (0.998866-0.046178)/0.995000 = 0.957474 * att4: (48.622165-0.202530)/50.000000 = 0.968393 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 9 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 10 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 14000 Output 2 called output2 range: 0 to 2 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 **************************************************************** * * 9 points. Chose rsnum -1 (thus using 9 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 50 600 0.319394 50 * experiment 254.178 15.209 3.88999 0.0773148 2.88868 * est rs center 298.621 27.8436 276.236 0.467758 24.3201 * est rs spread 53.9791 14.35 177.814 0.294083 14.6519 * * ------------------------------ * att0: (398.474500-204.602941)/200.000000 = 0.969358 * att1: (49.913921-1.856906)/49.000000 = 0.980755 * att2: (590.964103-0.046981)/600.000000 = 0.984862 * att3: (0.982304-0.014462)/0.995000 = 0.972706 * att4: (49.837130-0.922166)/50.000000 = 0.978299 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 10 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 14000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 **************************************************************** * * 10 points. Chose rsnum -1 (thus using 10 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 50 600 0.173875 50 * experiment 267.574 9.94783 532.478 0.0295892 4.29306 * est rs center 294.612 26.2899 302.594 0.486715 24.5429 * est rs spread 60.2726 14.0561 165.33 0.300102 14.6079 * * ------------------------------ * att0: (398.611022-202.586034)/200.000000 = 0.980125 * att1: (49.671068-2.103366)/49.000000 = 0.970769 * att2: (581.645204-1.113583)/600.000000 = 0.967553 * att3: (0.989484-0.008032)/0.995000 = 0.986384 * att4: (49.612211-0.060147)/50.000000 = 0.991041 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 11 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 14000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 **************************************************************** * * 11 points. Chose rsnum -1 (thus using 11 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 1 600 0.005 0 * experiment 365.544 42.3531 551.872 0.631122 25.6141 * est rs center 293.013 22.4167 317.568 0.541168 23.8188 * est rs spread 57.2839 12.961 182.401 0.263662 14.0807 * * ------------------------------ * att0: (399.608881-203.411810)/200.000000 = 0.980985 * att1: (48.852848-1.039882)/49.000000 = 0.975775 * att2: (599.885615-7.853271)/600.000000 = 0.986721 * att3: (0.979478-0.024934)/0.995000 = 0.959340 * att4: (49.391974-0.699439)/50.000000 = 0.973851 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 12 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 14000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 **************************************************************** * * 12 points. Chose rsnum -1 (thus using 12 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 50 600 0.005 50 * experiment 205.445 49.3628 587.255 0.0134481 48.5061 * est rs center 296.16 25.1528 331.451 0.491119 25.3148 * est rs spread 59.0391 14.2619 165.2 0.275261 15.4271 * * ------------------------------ * att0: (396.926647-200.622517)/200.000000 = 0.981521 * att1: (48.935032-1.204732)/49.000000 = 0.974088 * att2: (599.851330-17.476369)/600.000000 = 0.970625 * att3: (0.991416-0.011164)/0.995000 = 0.985178 * att4: (49.720954-0.043910)/50.000000 = 0.993541 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 13 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 14000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 **************************************************************** * * 13 points. Chose rsnum -1 (thus using 13 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 1 600 1 0 * experiment 204.263 43.4142 541.387 0.799924 6.77785 * est rs center 301.208 24.8709 289.806 0.512036 26.7348 * est rs spread 56.5386 14.2793 173.295 0.288742 13.2149 * * ------------------------------ * att0: (398.495770-201.295172)/200.000000 = 0.986003 * att1: (49.591819-1.103012)/49.000000 = 0.989567 * att2: (596.998891-5.281168)/600.000000 = 0.986196 * att3: (0.998446-0.008389)/0.995000 = 0.995032 * att4: (49.540927-0.312524)/50.000000 = 0.984568 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 14 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 14000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 **************************************************************** * * 14 points. Chose rsnum -1 (thus using 14 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 1 600 0.998829 0 * experiment 202.672 1.73824 582.467 0.983769 0.00667194 * est rs center 296.154 25.5573 293.387 0.476715 24.1696 * est rs spread 55.6337 13.4807 173.587 0.279647 14.5561 * * ------------------------------ * att0: (399.105797-202.963664)/200.000000 = 0.980711 * att1: (49.344836-1.840190)/49.000000 = 0.969483 * att2: (599.118599-17.194673)/600.000000 = 0.969873 * att3: (0.983355-0.008446)/0.995000 = 0.979807 * att4: (49.406919-0.580590)/50.000000 = 0.976527 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 15 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 14000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 **************************************************************** * * 15 points. Chose rsnum -1 (thus using 15 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 50 600 1 50 * experiment 290.335 34.4914 190.068 0.706402 0.576097 * est rs center 305.699 25.0261 275.546 0.486417 25.9108 * est rs spread 56.8867 14.6489 178.02 0.297613 14.1259 * * ------------------------------ * att0: (398.614383-206.859399)/200.000000 = 0.958775 * att1: (49.076422-1.386219)/49.000000 = 0.973269 * att2: (599.276009-5.958916)/600.000000 = 0.988862 * att3: (0.998099-0.005803)/0.995000 = 0.997282 * att4: (49.864703-1.382395)/50.000000 = 0.969646 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 16 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 14000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 **************************************************************** * * 16 points. Chose rsnum -1 (thus using 16 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 50 600 1 48.3085 * experiment 385.175 18.5293 33.5188 0.881389 11.2985 * est rs center 305.058 25.9212 293.755 0.481703 22.2316 * est rs spread 61.1422 14.1544 187.276 0.299417 13.8352 * * ------------------------------ * att0: (395.994267-201.337444)/200.000000 = 0.973284 * att1: (49.514940-1.458696)/49.000000 = 0.980740 * att2: (596.620713-11.726673)/600.000000 = 0.974823 * att3: (0.979347-0.025418)/0.995000 = 0.958723 * att4: (49.910258-0.354814)/50.000000 = 0.991109 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 17 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 **************************************************************** * * 17 points. Chose rsnum -1 (thus using 17 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 50 600 1 40.2154 * experiment 205.775 25.7313 301.562 0.244123 18.6406 * est rs center 301.953 26.9517 317.41 0.510041 25.1993 * est rs spread 56.8376 14.9728 160.183 0.289366 14.911 * * ------------------------------ * att0: (396.096703-200.208615)/200.000000 = 0.979440 * att1: (49.930883-1.097005)/49.000000 = 0.996610 * att2: (592.414480-2.454292)/600.000000 = 0.983267 * att3: (0.979537-0.030543)/0.995000 = 0.953763 * att4: (49.653847-1.172325)/50.000000 = 0.969630 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 18 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 **************************************************************** * * 18 points. Chose rsnum -1 (thus using 18 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 1 600 0.005 15.3176 * experiment 316.763 43.5425 579.874 0.979116 0.8255 * est rs center 308.609 25.8771 302.359 0.473619 24.0118 * est rs spread 62.3008 13.2743 179.626 0.283865 14.0238 * * ------------------------------ * att0: (399.887250-200.103473)/200.000000 = 0.998919 * att1: (49.952136-1.133469)/49.000000 = 0.996299 * att2: (594.645324-2.893475)/600.000000 = 0.986253 * att3: (0.994714-0.006398)/0.995000 = 0.993283 * att4: (49.929408-0.727765)/50.000000 = 0.984033 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 19 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 **************************************************************** * * 19 points. Chose rsnum -1 (thus using 19 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 24.5946 567.442 0.005 50 * experiment 375.019 2.29124 312.068 0.0273584 40.8324 * est rs center 308.134 25.0255 304.157 0.479445 23.8133 * est rs spread 56.7955 14.1927 156.033 0.285157 15.1041 * * ------------------------------ * att0: (399.698677-202.278861)/200.000000 = 0.987099 * att1: (49.518141-1.127980)/49.000000 = 0.987554 * att2: (594.103990-5.252601)/600.000000 = 0.981419 * att3: (0.980752-0.018480)/0.995000 = 0.967107 * att4: (49.971419-0.191541)/50.000000 = 0.995598 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 20 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 **************************************************************** * * 20 points. Chose rsnum -1 (thus using 20 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 1 0 1 50 * experiment 203.197 2.30557 16.7346 0.998439 49.7053 * est rs center 310.874 26.9791 313 0.568884 23.074 * est rs spread 60.1805 15.7205 177.865 0.300793 14.3844 * * ------------------------------ * att0: (398.700865-206.888977)/200.000000 = 0.959059 * att1: (49.992789-1.682681)/49.000000 = 0.985921 * att2: (593.782499-3.396475)/600.000000 = 0.983977 * att3: (0.999762-0.008849)/0.995000 = 0.995892 * att4: (48.931760-1.718866)/50.000000 = 0.944258 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 21 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 **************************************************************** * * 21 points. Chose rsnum 0 (thus using 21 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 400 31.5763 600 1 0 * experiment 399.362 32.0546 596.477 0.994731 0.747495 * est rs center 300.171 24.9676 288.844 0.512693 25.7077 * est rs spread 56.7083 14.4105 175.995 0.26991 14.4277 * * Newtiness: 0.785071 * E(rec): -1017.4 -106616 18.9632=> 1017.395071 * E(expt): -1010.43 -105990 18.8945=> 1010.431605 * * ------------------------------ * att0: (398.167548-202.564988)/200.000000 = 0.978013 * att1: (49.823861-1.157566)/49.000000 = 0.993190 * att2: (596.308615-3.932127)/600.000000 = 0.987294 * att3: (0.995794-0.010647)/0.995000 = 0.990098 * att4: (49.550060-1.183952)/50.000000 = 0.967322 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 22 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 **************************************************************** * * 22 points. Chose rsnum -1 (thus using 22 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 25.451 600 0.005 27.2369 * experiment 228.722 6.61812 15.0531 0.957437 3.94265 * est rs center 300.77 24.7992 308.761 0.500162 25.789 * est rs spread 54.9158 13.8605 175.355 0.296794 15.0309 * * ------------------------------ * att0: (395.393309-200.409631)/200.000000 = 0.974918 * att1: (49.790163-1.184090)/49.000000 = 0.991961 * att2: (598.662563-4.954066)/600.000000 = 0.989514 * att3: (0.990927-0.005845)/0.995000 = 0.990033 * att4: (49.278597-1.390517)/50.000000 = 0.957762 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 23 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 **************************************************************** * * 23 points. Chose rsnum -1 (thus using 23 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 26.6392 600 0.005 25.0278 * experiment 392.839 1.57322 49.8528 0.103513 23.1365 * est rs center 292.823 21.6392 297.13 0.489557 26.2438 * est rs spread 59.8216 14.803 168.346 0.282991 14.0232 * * ------------------------------ * att0: (399.216479-200.239970)/200.000000 = 0.994883 * att1: (49.841502-1.616667)/49.000000 = 0.984180 * att2: (592.707469-3.667560)/600.000000 = 0.981733 * att3: (0.999341-0.006260)/0.995000 = 0.998071 * att4: (48.336034-0.388093)/50.000000 = 0.958959 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 24 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 **************************************************************** * * 24 points. Chose rsnum 0 (thus using 24 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 23.8779 600 0.005 21.4989 * experiment 203.192 23.2049 583.412 0.0274361 21.1055 * est rs center 304.066 28.6829 326.972 0.515004 25.4662 * est rs spread 54.1548 12.5552 175.855 0.283991 12.8422 * * Newtiness: 0.233178 * E(rec): -88.7002 -6430 4.39157=> 88.700206 * E(expt): -87.0323 -6408.87 4.40329=> 87.032313 * * ------------------------------ * att0: (399.205979-201.180234)/200.000000 = 0.990129 * att1: (49.820857-1.616302)/49.000000 = 0.983766 * att2: (599.401256-0.640417)/600.000000 = 0.997935 * att3: (0.992850-0.005336)/0.995000 = 0.992476 * att4: (49.878598-0.320245)/50.000000 = 0.991167 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 25 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 **************************************************************** * * 25 points. Chose rsnum -1 (thus using 25 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 50 485.798 1 50 * experiment 314.357 49.3846 63.2885 0.297228 42.3151 * est rs center 289.12 27.3805 327.286 0.584965 26.4246 * est rs spread 57.104 14.2083 169.162 0.265921 14.937 * * ------------------------------ * att0: (398.928770-202.045739)/200.000000 = 0.984415 * att1: (49.698589-1.342915)/49.000000 = 0.986850 * att2: (599.352633-9.759659)/600.000000 = 0.982655 * att3: (0.999228-0.038804)/0.995000 = 0.965250 * att4: (49.299626-0.831185)/50.000000 = 0.969369 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 26 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 **************************************************************** * * 26 points. Chose rsnum 0 (thus using 26 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 12.3554 600 0.005 0 * experiment 380.646 49.828 201.176 0.395427 9.40307 * est rs center 305.289 25.7918 292.644 0.468975 25.7737 * est rs spread 59.905 14.5353 169.527 0.28335 14.4522 * * Newtiness: 0.000000 * E(rec): -69.9987 -5209.84 3.2221=> 69.998663 * E(expt): -58.9209 5148.52 -4.02367=> 58.920934 * * ------------------------------ * att0: (399.663685-200.454628)/200.000000 = 0.996045 * att1: (49.454050-1.945939)/49.000000 = 0.969553 * att2: (598.190567-6.580657)/600.000000 = 0.986017 * att3: (0.988715-0.008670)/0.995000 = 0.984970 * att4: (48.916953-0.001301)/50.000000 = 0.978313 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 27 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 **************************************************************** * * 27 points. Chose rsnum 1 (thus using 26 points) * Of 102 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.9804 * base 200 1 600 0.005 0 * experiment 247.343 5.70226 397.956 0.527813 49.1318 * est rs center 297.095 23.4376 303.886 0.53167 25.7541 * est rs spread 53.7709 14.4129 164.058 0.287235 14.5005 * * Newtiness: 0.000000 * E(rec): -64.6326 -2463.69 3.05696=> 64.632594 * E(expt): 12.9961 14774.2 3.20605=> -12.996124 * * ------------------------------ * att0: (399.865189-207.352651)/200.000000 = 0.962563 * att1: (49.387909-1.278022)/49.000000 = 0.981834 * att2: (597.226363-6.797806)/600.000000 = 0.984048 * att3: (0.972261-0.020464)/0.995000 = 0.956579 * att4: (49.711616-0.912437)/50.000000 = 0.975984 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 28 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 **************************************************************** * * 28 points. Chose rsnum 4 (thus using 24 points) * Of 103 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.9709 * base 200 50 387.169 1 50 * experiment 204.619 49.437 382.88 0.973145 49.9484 * est rs center 305.143 24.8898 310.771 0.538965 22.8897 * est rs spread 55.0107 14.0239 179.902 0.264061 14.233 * * Newtiness: 0.000000 * E(rec): -250.293 3290.72 -1.10593=> 250.293419 * E(expt): -238.197 3646.34 -1.37112=> 238.197130 * * ------------------------------ * att0: (397.727585-203.426883)/200.000000 = 0.971504 * att1: (49.978443-1.205983)/49.000000 = 0.995356 * att2: (596.544473-19.182291)/600.000000 = 0.962270 * att3: (0.999448-0.075448)/0.995000 = 0.928644 * att4: (49.263463-0.962598)/50.000000 = 0.966017 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 29 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 **************************************************************** * * 29 points. Chose rsnum 1 (thus using 28 points) * Of 100 random points, 100 were inside rstat * Estimated rstat fractional volume is 1.0000 * base 200 1 600 0.150388 0 * experiment 204.894 1.83935 588.626 0.142092 0.114791 * est rs center 302.661 22.8913 283.723 0.530187 25.6104 * est rs spread 57.7733 12.4708 171.921 0.290793 14.3424 * * Newtiness: 0.678921 * E(rec): -65.263 -4639.34 3.08836=> 65.263047 * E(expt): -68.2095 -5202.15 2.88172=> 68.209490 * * ------------------------------ * att0: (397.155715-200.751420)/200.000000 = 0.982021 * att1: (47.143355-1.382699)/49.000000 = 0.933891 * att2: (592.836064-4.209536)/600.000000 = 0.981044 * att3: (0.996417-0.019234)/0.995000 = 0.982093 * att4: (48.015474-0.025539)/50.000000 = 0.959799 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 30 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 **************************************************************** * * 30 points. Chose rsnum 2 (thus using 28 points) * Of 104 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.9615 * base 200 8.63456 588.526 0.005 50 * experiment 203.682 9.29726 583.766 0.010048 49.6652 * est rs center 300.071 24.0332 282.044 0.509923 23.9425 * est rs spread 56.6929 15.6517 175.218 0.284417 14.4144 * * Newtiness: 0.000000 * E(rec): 0.878275 5582.8 5.97475=> -0.878275 * E(expt): -0.101068 5375.31 5.83591=> 0.101068 * * ------------------------------ * att0: (397.840619-200.039366)/200.000000 = 0.989006 * att1: (49.843291-1.012514)/49.000000 = 0.996546 * att2: (596.046180-16.425304)/600.000000 = 0.966035 * att3: (0.998981-0.041309)/0.995000 = 0.962485 * att4: (49.537275-0.265208)/50.000000 = 0.985441 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 31 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 **************************************************************** * * 31 points. Chose rsnum 5 (thus using 26 points) * Of 117 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.8547 * base 400 47.8416 600 0.005 0 * experiment 399.172 47.26 593.505 0.0308236 1.05896 * est rs center 296.788 25.5241 322.272 0.481658 23.2848 * est rs spread 58.9571 13.4798 159.793 0.290004 14.7802 * * Newtiness: 0.341848 * E(rec): -113.129 -21746.3 4.20127=> 113.128852 * E(expt): -103.111 -20536.5 4.28579=> 103.110863 * * ------------------------------ * att0: (398.558320-206.815121)/200.000000 = 0.958716 * att1: (49.975910-1.682404)/49.000000 = 0.985582 * att2: (592.012107-13.681356)/600.000000 = 0.963885 * att3: (0.999333-0.017853)/0.995000 = 0.986412 * att4: (49.250108-0.667091)/50.000000 = 0.971660 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 32 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 **************************************************************** * * 32 points. Chose rsnum 8 (thus using 24 points) * Of 141 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.7092 * base 200 50 218.274 0.005 50 * experiment 205.4 49.6588 221.578 0.0327483 48.918 * est rs center 296.591 24.5746 355.689 0.472541 24.9376 * est rs spread 62.195 15.2025 138.492 0.279508 14.7222 * * Newtiness: 0.800398 * E(rec): 216.53 21891.7 4.14884=> -216.530431 * E(expt): 223.941 22796.2 4.2122=> -223.941137 * * ------------------------------ * att0: (398.352086-200.216265)/200.000000 = 0.990679 * att1: (49.952177-1.170706)/49.000000 = 0.995540 * att2: (597.412381-63.023610)/600.000000 = 0.890648 * att3: (0.999566-0.007702)/0.995000 = 0.996848 * att4: (49.963080-1.452830)/50.000000 = 0.970205 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 33 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 **************************************************************** * * 33 points. Chose rsnum 7 (thus using 26 points) * Of 111 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.9009 * base 200 15.1137 572.804 0.214986 30.2285 * experiment 204.619 15.0504 569.281 0.225063 30.6426 * est rs center 291.546 24.3047 324.319 0.454487 24.7403 * est rs spread 57.271 14.4509 157.236 0.294808 15.1292 * * Newtiness: 0.390148 * E(rec): 112.352 15681.7 1.90969=> -112.351837 * E(expt): 113.546 15896.2 1.87294=> -113.545791 * * ------------------------------ * att0: (399.666628-200.373634)/200.000000 = 0.996465 * att1: (48.834088-1.122703)/49.000000 = 0.973702 * att2: (590.213022-44.279654)/600.000000 = 0.909889 * att3: (0.995689-0.006851)/0.995000 = 0.993807 * att4: (49.640916-0.518754)/50.000000 = 0.982443 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 34 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 **************************************************************** * * 34 points. Chose rsnum 6 (thus using 28 points) * Of 106 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.9434 * base 200 16.0467 506.798 0.005 41.7901 * experiment 376.241 3.22238 325.177 0.558168 8.65972 * est rs center 292.176 27.0395 294.631 0.501415 23.8117 * est rs spread 53.2988 13.4043 152.939 0.289442 15.0434 * * Newtiness: 0.000000 * E(rec): 79.1833 7899.17 3.73705=> -79.183276 * E(expt): -5.23579 -4558.91 6.58127=> 5.235790 * * ------------------------------ * att0: (398.355169-202.330858)/200.000000 = 0.980122 * att1: (49.534507-1.930340)/49.000000 = 0.971514 * att2: (597.268379-16.594760)/600.000000 = 0.967789 * att3: (0.996311-0.007104)/0.995000 = 0.994178 * att4: (49.507007-1.504629)/50.000000 = 0.960048 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 35 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 **************************************************************** * * 35 points. Chose rsnum 9 (thus using 26 points) * Of 109 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.9174 * base 200 26.8628 428.103 0.005 50 * experiment 203.194 26.1716 435.073 0.0347906 48.7059 * est rs center 293.09 23.6148 316.79 0.524483 25.6773 * est rs spread 55.663 13.0436 147.217 0.309183 14.1903 * * Newtiness: 0.301151 * E(rec): 18.3135 869.536 5.87426=> -18.313513 * E(expt): 22.7905 1444.8 5.80559=> -22.790547 * * ------------------------------ * att0: (395.655558-201.230888)/200.000000 = 0.972123 * att1: (49.748975-1.165807)/49.000000 = 0.991493 * att2: (591.019951-32.728650)/600.000000 = 0.930486 * att3: (0.998386-0.021486)/0.995000 = 0.981809 * att4: (49.931307-0.157246)/50.000000 = 0.995481 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 36 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 **************************************************************** * * 36 points. Chose rsnum 5 (thus using 31 points) * Of 109 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.9174 * base 200 1 528.435 0.005 31.3087 * experiment 205.546 2.17061 519.46 0.0296824 31.2049 * est rs center 294.981 24.4484 322.699 0.512329 24.4522 * est rs spread 59.4394 14.5755 164.839 0.290696 14.7019 * * Newtiness: 0.799893 * E(rec): -3.35515 416.577 4.31901=> 3.355145 * E(expt): -5.13089 285.66 4.32834=> 5.130891 * * ------------------------------ * att0: (398.136007-200.694801)/200.000000 = 0.987206 * att1: (49.527913-1.200757)/49.000000 = 0.986268 * att2: (590.582626-20.441642)/600.000000 = 0.950235 * att3: (0.999659-0.005123)/0.995000 = 0.999534 * att4: (49.801895-0.061990)/50.000000 = 0.994798 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 37 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 **************************************************************** * * 37 points. Chose rsnum 6 (thus using 31 points) * Of 105 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.9524 * base 200 18.8297 600 0.281881 22.1865 * experiment 201.552 18.7809 591.497 0.287625 22.5668 * est rs center 296.887 27.6239 332.374 0.534145 23.3805 * est rs spread 61.9105 12.7923 155.283 0.259727 15.164 * * Newtiness: 0.813326 * E(rec): 28.5045 2011.45 3.85795=> -28.504474 * E(expt): 27.6074 1916.3 3.77942=> -27.607392 * * ------------------------------ * att0: (399.470008-200.076114)/200.000000 = 0.996969 * att1: (49.689039-2.013761)/49.000000 = 0.972965 * att2: (598.525643-26.231176)/600.000000 = 0.953824 * att3: (0.987667-0.058555)/0.995000 = 0.933781 * att4: (49.262191-0.014928)/50.000000 = 0.984945 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 38 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 **************************************************************** * * 38 points. Chose rsnum 10 (thus using 28 points) * Of 130 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.7692 * base 200 27.4482 451.895 0.005 50 * experiment 281.001 45.3525 250.485 0.19281 25.5239 * est rs center 296.223 23.5354 381.286 0.528671 25.9068 * est rs spread 55.3409 13.9916 144.382 0.290701 14.0707 * * Newtiness: 0.000000 * E(rec): 61.8961 8451.49 5.06046=> -61.896073 * E(expt): 75.7241 9341.18 3.97825=> -75.724095 * * ------------------------------ * att0: (394.978710-200.942367)/200.000000 = 0.970182 * att1: (48.855514-1.384123)/49.000000 = 0.968804 * att2: (596.354187-59.676221)/600.000000 = 0.894463 * att3: (0.992587-0.005172)/0.995000 = 0.992377 * att4: (49.934394-0.244930)/50.000000 = 0.993789 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 39 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 **************************************************************** * * 39 points. Chose rsnum 8 (thus using 31 points) * Of 116 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.8621 * base 400 9.578 600 0.357875 0 * experiment 395.957 8.9091 586.088 0.370943 0.500009 * est rs center 301.7 24.499 332.515 0.511524 24.7012 * est rs spread 53.6463 14.3735 164.004 0.322358 15.3652 * * Newtiness: 0.000000 * E(rec): -39.2378 3949.39 7.31653=> 39.237793 * E(expt): -34.3848 4272.42 7.15294=> 34.384760 * * ------------------------------ * att0: (395.916456-201.323564)/200.000000 = 0.972964 * att1: (49.892138-1.162751)/49.000000 = 0.994477 * att2: (598.788036-26.768728)/600.000000 = 0.953366 * att3: (0.998513-0.007043)/0.995000 = 0.996451 * att4: (49.749732-0.444084)/50.000000 = 0.986113 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 40 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 **************************************************************** * * 40 points. Chose rsnum 12 (thus using 28 points) * Of 153 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.6536 * base 200 26.697 480.092 0.005 50 * experiment 200.46 26.2194 484.104 0.0109965 49.5818 * est rs center 296.823 26.6948 401.358 0.497698 24.7444 * est rs spread 54.3386 13.8349 113.885 0.307641 14.4393 * * Newtiness: 0.421162 * E(rec): 46.9128 10163 1.66352=> -46.912787 * E(expt): 47.7629 10264.5 1.65652=> -47.762925 * * ------------------------------ * att0: (397.161608-201.770693)/200.000000 = 0.976955 * att1: (49.997002-1.069619)/49.000000 = 0.998518 * att2: (599.915518-110.814850)/600.000000 = 0.815168 * att3: (0.993425-0.005699)/0.995000 = 0.992690 * att4: (49.354797-2.209284)/50.000000 = 0.942910 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 41 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 **************************************************************** * * 41 points. Chose rsnum 10 (thus using 31 points) * Of 145 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.6897 * base 200 28.0129 454.714 0.005 50 * experiment 248.3 43.0583 397.799 0.250077 0.108124 * est rs center 292.882 22.3976 392.555 0.470415 23.8969 * est rs spread 59.2468 14.8228 135.696 0.28522 13.7333 * * Newtiness: 0.000000 * E(rec): 72.6644 13967 3.4037=> -72.664372 * E(expt): 47.4918 9931.38 2.9708=> -47.491798 * * ------------------------------ * att0: (396.393498-200.256427)/200.000000 = 0.980685 * att1: (49.357582-1.375820)/49.000000 = 0.979220 * att2: (599.486986-103.656683)/600.000000 = 0.826384 * att3: (0.975842-0.028802)/0.995000 = 0.951799 * att4: (48.002245-1.207699)/50.000000 = 0.935891 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 42 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 **************************************************************** * * 42 points. Chose rsnum 18 (thus using 24 points) * Of 194 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.5155 * base 201.552 18.7809 591.497 0.287625 22.5668 * experiment 214.421 47.0541 253.233 0.187376 28.3728 * est rs center 299.902 27.5154 435.03 0.529981 20.8317 * est rs spread 60.3192 13.1148 93.0847 0.291303 14.2782 * * Newtiness: 0.556733 * E(rec): 76.6451 10818.3 9.9225=> -76.645052 * E(expt): 160.222 17390.3 11.1985=> -160.222294 * * ------------------------------ * att0: (394.868934-202.016599)/200.000000 = 0.964262 * att1: (49.872700-2.966232)/49.000000 = 0.957275 * att2: (597.885962-237.095394)/600.000000 = 0.601318 * att3: (0.994085-0.005367)/0.995000 = 0.993687 * att4: (49.503756-0.771665)/50.000000 = 0.974642 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 43 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 **************************************************************** * * 43 points. Chose rsnum 12 (thus using 31 points) * Of 159 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.6289 * base 200 23.0211 449.325 0.005 0 * experiment 200.056 36.1729 281.748 0.42356 48.2204 * est rs center 297.207 25.3448 425.363 0.501556 23.9478 * est rs spread 58.0379 14.8115 115.63 0.315714 15.5684 * * Newtiness: 0.000000 * E(rec): 72.6532 12166 3.91342=> -72.653245 * E(expt): 45.5089 9765.15 8.79683=> -45.508908 * * ------------------------------ * att0: (398.329271-200.029441)/200.000000 = 0.991499 * att1: (49.894630-1.254962)/49.000000 = 0.992646 * att2: (593.943611-178.147975)/600.000000 = 0.692993 * att3: (0.994860-0.013158)/0.995000 = 0.986635 * att4: (49.194127-0.185529)/50.000000 = 0.980172 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 44 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 **************************************************************** * * 44 points. Chose rsnum 10 (thus using 34 points) * Of 158 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.6329 * base 200 39.1141 450.782 0.005 50 * experiment 203.181 39.3625 446.439 0.0141574 48.7948 * est rs center 295.16 25.0292 373.902 0.470712 26.3025 * est rs spread 56.8727 13.7819 130.672 0.292138 13.4331 * * Newtiness: 0.431237 * E(rec): 137.909 21542.3 5.91198=> -137.908702 * E(expt): 136.32 21319.2 5.76311=> -136.320197 * * ------------------------------ * att0: (398.638850-201.926653)/200.000000 = 0.983561 * att1: (49.922409-1.170061)/49.000000 = 0.994946 * att2: (591.915720-118.547903)/600.000000 = 0.788946 * att3: (0.981416-0.010691)/0.995000 = 0.975603 * att4: (49.791855-1.425496)/50.000000 = 0.967327 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 45 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 **************************************************************** * * 45 points. Chose rsnum 19 (thus using 26 points) * Of 237 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.4219 * base 203.192 23.2049 583.412 0.0274361 21.1055 * experiment 302.059 30.296 586.763 0.199072 37.3792 * est rs center 280.903 26.629 442.432 0.497872 25.6061 * est rs spread 47.0274 15.1498 96.9574 0.269419 15.3375 * * Newtiness: 0.000000 * E(rec): -16.2527 -5974.71 0.525085=> 16.252706 * E(expt): 11.3738 -4304.34 1.13318=> -11.373842 * * ------------------------------ * att0: (381.883072-200.565827)/200.000000 = 0.906586 * att1: (49.087047-1.359988)/49.000000 = 0.974022 * att2: (585.553042-258.947372)/600.000000 = 0.544343 * att3: (0.997529-0.007509)/0.995000 = 0.994994 * att4: (49.265983-0.168983)/50.000000 = 0.981940 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 46 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 **************************************************************** * * 46 points. Chose rsnum 12 (thus using 34 points) * Of 130 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.7692 * base 299.927 17.9722 600 0.690745 0 * experiment 296.993 17.9238 582.318 0.694765 1.3157 * est rs center 300.561 21.9009 348.279 0.516103 23.6165 * est rs spread 59.5452 13.723 151.309 0.270987 15.365 * * Newtiness: 0.316167 * E(rec): -44.4588 -563.749 8.38436=> 44.458816 * E(expt): -38.0004 247.287 8.1392=> 38.000353 * * ------------------------------ * att0: (399.442518-200.822688)/200.000000 = 0.993099 * att1: (49.321955-1.400196)/49.000000 = 0.977995 * att2: (599.196208-51.497656)/600.000000 = 0.912831 * att3: (0.994370-0.042025)/0.995000 = 0.957130 * att4: (49.921945-0.245960)/50.000000 = 0.993520 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 47 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 **************************************************************** * * 47 points. Chose rsnum 21 (thus using 26 points) * Of 214 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.4673 * base 203.194 26.1716 435.073 0.0347906 48.7059 * experiment 322.801 6.72765 579.885 0.0318424 28.474 * est rs center 292.075 26.1656 439.921 0.546128 24.5819 * est rs spread 55.1471 12.9813 90.1061 0.267894 15.4536 * * Newtiness: 0.000000 * E(rec): -416.176 -63145.2 31.2994=> 416.176303 * E(expt): -724.646 -103854 41.8852=> 724.646300 * * ------------------------------ * att0: (398.865932-201.531105)/200.000000 = 0.986674 * att1: (49.670453-1.028890)/49.000000 = 0.992685 * att2: (598.159544-287.233217)/600.000000 = 0.518211 * att3: (0.991368-0.022627)/0.995000 = 0.973608 * att4: (49.860853-0.600992)/50.000000 = 0.985197 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 48 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 **************************************************************** * * 48 points. Chose rsnum 10 (thus using 38 points) * Of 122 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.8197 * base 200 36.4336 600 0.005 10.3151 * experiment 267.98 1.64609 342.672 0.0886483 20.503 * est rs center 281.739 27.6702 368.987 0.538894 23.9595 * est rs spread 51.1037 14.4013 145.918 0.30568 13.8696 * * Newtiness: 0.000000 * E(rec): 33.1102 5877.73 1.58378=> -33.110243 * E(expt): 49.6628 9710.73 1.64038=> -49.662779 * * ------------------------------ * att0: (398.435482-201.915061)/200.000000 = 0.982602 * att1: (49.767296-1.098327)/49.000000 = 0.993244 * att2: (598.483256-23.693223)/600.000000 = 0.957983 * att3: (0.996239-0.008701)/0.995000 = 0.992501 * att4: (49.822498-0.560150)/50.000000 = 0.985247 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 49 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 **************************************************************** * * 49 points. Chose rsnum 11 (thus using 38 points) * Of 138 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.7246 * base 200 44.1458 600 0.005 23.6 * experiment 264.817 15.9467 185.121 0.980683 30.3817 * est rs center 284.164 28.0668 372.342 0.576255 21.6881 * est rs spread 53.704 14.1791 157.975 0.292572 14.0362 * * Newtiness: 0.000000 * E(rec): -3.2585 1012 5.14204=> 3.258504 * E(expt): 89.8006 15375 7.85232=> -89.800568 * * ------------------------------ * att0: (399.757082-201.526596)/200.000000 = 0.991152 * att1: (49.965738-1.696559)/49.000000 = 0.985085 * att2: (596.682985-21.501068)/600.000000 = 0.958637 * att3: (0.999435-0.005622)/0.995000 = 0.998807 * att4: (49.244441-0.059459)/50.000000 = 0.983700 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 50 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 20000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 **************************************************************** * * 50 points. Chose rsnum 12 (thus using 38 points) * Of 141 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.7092 * base 200 36.8202 600 0.194541 28.8191 * experiment 201.464 36.141 596.515 0.200096 29.1826 * est rs center 284.484 25.7535 365.582 0.479039 24.6679 * est rs spread 51.1577 12.7972 147.43 0.278962 14.2112 * * Newtiness: 0.327029 * E(rec): 3.78333 4078.44 7.02107=> -3.783330 * E(expt): 3.76217 4131.49 7.01812=> -3.762169 * * ------------------------------ * att0: (397.301225-200.397167)/200.000000 = 0.984520 * att1: (49.285026-1.398675)/49.000000 = 0.977272 * att2: (597.126047-33.269052)/600.000000 = 0.939762 * att3: (0.984638-0.006494)/0.995000 = 0.983059 * att4: (49.832484-0.010981)/50.000000 = 0.996430 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 51 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 **************************************************************** * * 51 points. Chose rsnum 27 (thus using 24 points) * Of 271 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3690 * base 203.192 23.2049 583.412 0.0274361 21.1055 * experiment 204.382 46.1719 409.378 0.145584 10.844 * est rs center 290.438 26.0571 490.29 0.519563 24.249 * est rs spread 53.8797 14.1414 78.7528 0.28097 13.6948 * * Newtiness: 0.976826 * E(rec): 34.1721 -21292.8 65.7136=> -34.172063 * E(expt): -55.3869 -21257.9 44.5709=> 55.386936 * * ------------------------------ * att0: (397.370308-200.806688)/200.000000 = 0.982818 * att1: (49.442071-1.348808)/49.000000 = 0.981495 * att2: (597.804056-324.433965)/600.000000 = 0.455617 * att3: (0.971789-0.023058)/0.995000 = 0.953499 * att4: (49.342361-0.395654)/50.000000 = 0.978934 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 52 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 **************************************************************** * * 52 points. Chose rsnum 11 (thus using 41 points) * Of 142 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.7042 * base 200 46.4243 600 0.144713 29.2119 * experiment 205.94 46.305 596.759 0.132333 29.483 * est rs center 288.494 25.5364 378.272 0.505302 22.6247 * est rs spread 53.9862 14.1079 147.414 0.287432 13.7106 * * Newtiness: 0.083977 * E(rec): -16.4607 656.449 5.00185=> 16.460702 * E(expt): -15.1255 967.345 4.9282=> 15.125484 * * ------------------------------ * att0: (396.508585-201.461926)/200.000000 = 0.975233 * att1: (49.856076-1.242954)/49.000000 = 0.992105 * att2: (599.318690-38.648248)/600.000000 = 0.934451 * att3: (0.995133-0.008004)/0.995000 = 0.992089 * att4: (48.717812-0.266713)/50.000000 = 0.969022 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 53 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 **************************************************************** * * 53 points. Chose rsnum 25 (thus using 28 points) * Of 254 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3937 * base 203.192 23.2049 583.412 0.0274361 21.1055 * experiment 204.008 19.7683 392.493 0.933872 15.2219 * est rs center 285.277 25.3474 480.778 0.514796 20.1945 * est rs spread 54.6565 13.5317 81.0794 0.300624 14.0037 * * Newtiness: 0.000000 * E(rec): -310.581 -43579 6.95455=> 310.581081 * E(expt): -168.795 -24677.4 13.7216=> 168.795185 * * ------------------------------ * att0: (397.840445-200.182825)/200.000000 = 0.988288 * att1: (49.848223-1.338335)/49.000000 = 0.989998 * att2: (598.712601-304.756261)/600.000000 = 0.489927 * att3: (0.995150-0.011374)/0.995000 = 0.988720 * att4: (49.067302-0.374461)/50.000000 = 0.973857 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 54 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 **************************************************************** * * 54 points. Chose rsnum 13 (thus using 41 points) * Of 135 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.7407 * base 200 37.5269 600 1 27.3093 * experiment 204.964 2.92741 199.792 0.381504 22.6107 * est rs center 302.036 26.3388 415.881 0.484426 24.1108 * est rs spread 54.6154 13.7508 136.809 0.292546 14.1674 * * Newtiness: 0.000000 * E(rec): -43.9943 -3489.21 19.3783=> 43.994300 * E(expt): 34.8514 5815.76 4.93126=> -34.851364 * * ------------------------------ * att0: (398.118502-202.864496)/200.000000 = 0.976270 * att1: (49.850871-1.076331)/49.000000 = 0.995399 * att2: (597.025486-97.561403)/600.000000 = 0.832440 * att3: (0.991094-0.014660)/0.995000 = 0.981340 * att4: (49.328951-0.311884)/50.000000 = 0.980341 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 55 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 **************************************************************** * * 55 points. Chose rsnum 27 (thus using 28 points) * Of 275 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3636 * base 204.008 19.7683 392.493 0.933872 15.2219 * experiment 319.523 28.2997 464.851 0.29333 11.4258 * est rs center 278.243 27.1804 477.849 0.458829 24.1513 * est rs spread 49.9458 12.8272 72.3097 0.289156 13.5563 * * Newtiness: 0.000000 * E(rec): -181.305 -27237.1 29.6024=> 181.305375 * E(expt): -214.697 -33157.3 23.9222=> 214.697444 * * ------------------------------ * att0: (398.589192-203.586193)/200.000000 = 0.975015 * att1: (49.871383-1.379098)/49.000000 = 0.989638 * att2: (598.818477-338.151286)/600.000000 = 0.434445 * att3: (0.974216-0.010930)/0.995000 = 0.968127 * att4: (49.901897-0.360519)/50.000000 = 0.990828 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 56 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 **************************************************************** * * 56 points. Chose rsnum 18 (thus using 38 points) * Of 208 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.4808 * base 200 23.7214 365.631 0.005 0 * experiment 200.683 23.2865 374.606 0.0100224 0.459359 * est rs center 289.124 30.0466 410.828 0.445445 24.8046 * est rs spread 56.4283 14.2034 122.685 0.304239 14.7669 * * Newtiness: 0.484265 * E(rec): -0.067419 -507.848 5.46725=> 0.067419 * E(expt): -0.724021 -616.091 5.45543=> 0.724021 * * ------------------------------ * att0: (399.219545-200.000831)/200.000000 = 0.996094 * att1: (49.805590-1.559693)/49.000000 = 0.984610 * att2: (599.757385-98.378294)/600.000000 = 0.835632 * att3: (0.993359-0.016344)/0.995000 = 0.981925 * att4: (49.782443-0.006157)/50.000000 = 0.995526 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 57 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 **************************************************************** * * 57 points. Chose rsnum 33 (thus using 24 points) * Of 417 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.2398 * base 203.192 23.2049 583.412 0.0274361 21.1055 * experiment 326.539 14.965 543.042 0.950361 31.4343 * est rs center 276.789 24.6871 496.561 0.48327 19.3801 * est rs spread 51.2051 13.2254 64.4394 0.298488 14.0799 * * Newtiness: 0.000000 * E(rec): 27.2076 186.076 -25.9038=> -27.207591 * E(expt): 158.714 6069.13 -6.52766=> -158.714096 * * ------------------------------ * att0: (396.580866-201.161698)/200.000000 = 0.977096 * att1: (49.945731-1.535388)/49.000000 = 0.987966 * att2: (596.425898-373.302971)/600.000000 = 0.371872 * att3: (0.993608-0.008383)/0.995000 = 0.990176 * att4: (48.404667-0.632931)/50.000000 = 0.955435 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 58 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 **************************************************************** * * 58 points. Chose rsnum 32 (thus using 26 points) * Of 429 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.2331 * base 200.46 26.2194 484.104 0.0109965 49.5818 * experiment 295.212 24.7974 585.147 0.37322 6.70986 * est rs center 283.246 27.1626 505.427 0.470493 20.9988 * est rs spread 54.0195 13.5858 66.3986 0.273379 13.0418 * * Newtiness: 0.596781 * E(rec): 80.9527 1425.3 22.1184=> -80.952667 * E(expt): 75.1452 -829.604 21.8412=> -75.145233 * * ------------------------------ * att0: (397.209841-202.410369)/200.000000 = 0.973997 * att1: (49.762037-2.353927)/49.000000 = 0.967512 * att2: (599.476757-375.078384)/600.000000 = 0.373997 * att3: (0.955400-0.006799)/0.995000 = 0.953367 * att4: (48.916161-0.256517)/50.000000 = 0.973193 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 59 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 **************************************************************** * * 59 points. Chose rsnum 18 (thus using 41 points) * Of 170 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.5882 * base 276.092 28.1256 600 1 0 * experiment 255.126 4.80006 598.377 0.916888 22.4744 * est rs center 289.325 25.8646 408.402 0.457978 24.8342 * est rs spread 56.7677 14.1943 123.771 0.27399 14.246 * * Newtiness: 0.000000 * E(rec): -9.06284 -3214.33 7.5454=> 9.062845 * E(expt): 5.74099 -2852.7 7.92039=> -5.740989 * * ------------------------------ * att0: (396.075904-201.394904)/200.000000 = 0.973405 * att1: (48.701070-1.574249)/49.000000 = 0.961772 * att2: (597.016187-115.299923)/600.000000 = 0.802860 * att3: (0.997291-0.007038)/0.995000 = 0.995229 * att4: (49.233283-0.286632)/50.000000 = 0.978933 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 60 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 2.5 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 **************************************************************** * * 60 points. Chose rsnum 29 (thus using 31 points) * Of 273 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3663 * base 203.192 23.2049 583.412 0.0274361 21.1055 * experiment 266.302 21.3178 424.901 0.36614 1.93315 * est rs center 290.44 25.2371 484.679 0.486352 25.2431 * est rs spread 52.1757 13.6445 63.9639 0.296241 13.746 * * Newtiness: 0.416647 * E(rec): -211.325 -30433.2 37.6199=> 211.325310 * E(expt): -122.899 -17073.1 23.1759=> 122.899369 * * ------------------------------ * att0: (399.739937-201.307552)/200.000000 = 0.992162 * att1: (48.733866-1.663662)/49.000000 = 0.960616 * att2: (596.139159-376.886719)/600.000000 = 0.365421 * att3: (0.991967-0.006137)/0.995000 = 0.990784 * att4: (48.517549-0.018997)/50.000000 = 0.969971 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 61 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 3 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 **************************************************************** * * 61 points. Chose rsnum 33 (thus using 28 points) * Of 321 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3115 * base 346.187 50 600 0.005 0 * experiment 347.08 48.5486 592.938 0.0302987 0.1335 * est rs center 289.051 23.0735 493.764 0.44863 22.4236 * est rs spread 51.3896 14.1822 65.7217 0.283142 14.3798 * * Newtiness: 0.787415 * E(rec): 117.449 4451.17 51.9969=> -117.448604 * E(expt): 118.122 4565.66 51.9485=> -118.121851 * * ------------------------------ * att0: (395.511634-200.193739)/200.000000 = 0.976589 * att1: (49.335877-1.008024)/49.000000 = 0.986283 * att2: (596.600631-377.626249)/600.000000 = 0.364957 * att3: (0.997916-0.039261)/0.995000 = 0.963472 * att4: (49.547653-0.432739)/50.000000 = 0.982298 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 62 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 **************************************************************** * * 62 points. Chose rsnum 36 (thus using 26 points) * Of 435 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.2299 * base 282.384 36.1087 583.811 0.005 24.021 * experiment 282.351 36.0714 588.866 0.0131454 23.3144 * est rs center 283.515 26.4661 502.978 0.465792 20.4174 * est rs spread 59.9497 12.7193 62.3801 0.273433 12.9941 * * Newtiness: 0.123550 * E(rec): 97.1498 4978.27 62.3132=> -97.149792 * E(expt): 98.6221 4975.42 62.8847=> -98.622107 * * ------------------------------ * att0: (393.679411-200.493656)/200.000000 = 0.965929 * att1: (49.642235-1.193367)/49.000000 = 0.988752 * att2: (599.509650-396.423205)/600.000000 = 0.338477 * att3: (0.994948-0.010777)/0.995000 = 0.989117 * att4: (49.042488-0.995847)/50.000000 = 0.960933 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 63 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 **************************************************************** * * 63 points. Chose rsnum 35 (thus using 28 points) * Of 397 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.2519 * base 200 28.8146 387.861 1 0 * experiment 201.808 29.3112 386.075 0.992976 1.37274 * est rs center 288.062 27.9902 495.666 0.48412 19.4085 * est rs spread 54.092 13.0026 64.1374 0.294592 13.6309 * * Newtiness: 0.420325 * E(rec): 27.3985 -500.419 35.986=> -27.398509 * E(expt): 27.6225 -494.398 36.0003=> -27.622461 * * ------------------------------ * att0: (393.116325-202.776445)/200.000000 = 0.951699 * att1: (49.605966-1.651722)/49.000000 = 0.978658 * att2: (599.007882-370.289403)/600.000000 = 0.381197 * att3: (0.997286-0.007770)/0.995000 = 0.994489 * att4: (49.815375-0.288324)/50.000000 = 0.990541 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 64 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 **************************************************************** * * 64 points. Chose rsnum 33 (thus using 31 points) * Of 287 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3484 * base 282.351 36.0714 588.866 0.0131454 23.3144 * experiment 395.149 24.0369 521.669 0.0830863 10.33 * est rs center 269.872 26.0469 457.635 0.483173 20.5021 * est rs spread 51.6588 11.9724 99.5574 0.271516 13.2878 * * Newtiness: 0.000000 * E(rec): -20.8387 -2919.02 -4.65072=> 20.838669 * E(expt): -37.9501 -3561.01 -7.52053=> 37.950056 * * ------------------------------ * att0: (396.627451-201.780581)/200.000000 = 0.974234 * att1: (49.589204-3.830128)/49.000000 = 0.933859 * att2: (595.420055-184.757409)/600.000000 = 0.684438 * att3: (0.973823-0.017342)/0.995000 = 0.961288 * att4: (49.619229-0.040306)/50.000000 = 0.991578 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 65 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 **************************************************************** * * 65 points. Chose rsnum 34 (thus using 31 points) * Of 310 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3226 * base 282.351 36.0714 588.866 0.0131454 23.3144 * experiment 285.815 47.7596 353.792 0.706529 20.1181 * est rs center 272.315 27.8206 455.482 0.512923 22.0884 * est rs spread 47.0408 12.4058 98.7297 0.287737 14.486 * * Newtiness: 0.000000 * E(rec): -20.8387 -2919.02 -4.65072=> 20.838669 * E(expt): -0.248457 -1699.45 3.02979=> 0.248457 * * ------------------------------ * att0: (393.446836-201.946135)/200.000000 = 0.957504 * att1: (49.957188-4.916469)/49.000000 = 0.919198 * att2: (599.846446-230.706235)/600.000000 = 0.615234 * att3: (0.992496-0.016364)/0.995000 = 0.981037 * att4: (49.998769-0.038990)/50.000000 = 0.999196 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 66 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 **************************************************************** * * 66 points. Chose rsnum 35 (thus using 31 points) * Of 317 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3155 * base 282.351 36.0714 588.866 0.0131454 23.3144 * experiment 279.366 35.5011 588.992 0.0144512 23.66 * est rs center 268.597 26.5728 468.398 0.494941 20.541 * est rs spread 50.3008 14.4516 93.4194 0.30124 13.5032 * * Newtiness: 0.221697 * E(rec): -20.8387 -2919.02 -4.65072=> 20.838669 * E(expt): -18.9451 -2784.31 -4.61632=> 18.945106 * * ------------------------------ * att0: (389.710954-200.281013)/200.000000 = 0.947150 * att1: (49.702830-1.088197)/49.000000 = 0.992135 * att2: (596.704977-184.657168)/600.000000 = 0.686746 * att3: (0.999774-0.011922)/0.995000 = 0.992816 * att4: (49.450701-0.603867)/50.000000 = 0.976937 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 67 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 **************************************************************** * * 67 points. Chose rsnum 29 (thus using 38 points) * Of 298 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3356 * base 200 24.2794 491.727 0.1226 25.3497 * experiment 205.488 23.9977 494.075 0.136313 25.3711 * est rs center 277.289 27.2255 465.398 0.46723 20.5491 * est rs spread 48.3888 14.3013 95.9351 0.289433 13.0536 * * Newtiness: 0.507543 * E(rec): 30.0464 2797.39 6.35272=> -30.046384 * E(expt): 30.0933 2802.07 6.36829=> -30.093272 * * ------------------------------ * att0: (396.373892-202.665529)/200.000000 = 0.968542 * att1: (49.822372-2.100223)/49.000000 = 0.973921 * att2: (599.819819-156.483013)/600.000000 = 0.738895 * att3: (0.990209-0.017434)/0.995000 = 0.977664 * att4: (47.356423-0.097282)/50.000000 = 0.945183 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 68 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 **************************************************************** * * 68 points. Chose rsnum 30 (thus using 38 points) * Of 269 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3717 * base 200 29.6616 558.044 0.005 43.8337 * experiment 204.996 28.9681 550.725 0.00916434 44.025 * est rs center 269.245 28.5041 424.404 0.505657 19.7277 * est rs spread 47.8881 14.1951 94.9059 0.286384 13.0287 * * Newtiness: 0.963769 * E(rec): 31.7026 3428.98 9.09614=> -31.702614 * E(expt): 30.6057 3364.39 9.12209=> -30.605677 * * ------------------------------ * att0: (391.861742-200.414634)/200.000000 = 0.957236 * att1: (49.914048-1.059531)/49.000000 = 0.997031 * att2: (594.298653-208.140400)/600.000000 = 0.643597 * att3: (0.989636-0.012982)/0.995000 = 0.981561 * att4: (47.031242-0.172570)/50.000000 = 0.937173 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 69 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 **************************************************************** * * 69 points. Chose rsnum 35 (thus using 34 points) * Of 259 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3861 * base 200.46 26.2194 484.104 0.0109965 49.5818 * experiment 200.774 26.083 479.564 0.0284215 48.565 * est rs center 264.084 23.975 439.163 0.465446 20.4404 * est rs spread 45.7086 13.1676 98.9911 0.284637 13.0877 * * Newtiness: 0.399121 * E(rec): -22.1624 -552.449 -6.90594=> 22.162376 * E(expt): -22.1823 -605.895 -7.11714=> 22.182325 * * ------------------------------ * att0: (384.541021-200.414426)/200.000000 = 0.920633 * att1: (48.696304-1.416145)/49.000000 = 0.964901 * att2: (596.230079-229.377786)/600.000000 = 0.611420 * att3: (0.972989-0.005580)/0.995000 = 0.972271 * att4: (49.407842-0.382566)/50.000000 = 0.980506 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 70 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 **************************************************************** * * 70 points. Chose rsnum 24 (thus using 46 points) * Of 267 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3745 * base 200 34.9302 571.749 0.005 50 * experiment 200.517 34.7607 570.605 0.0051615 48.694 * est rs center 274.338 23.7994 412.858 0.480186 21.2418 * est rs spread 52.3936 12.6715 117.921 0.283877 13.1838 * * Newtiness: 0.217238 * E(rec): 13.5354 1288.69 16.742=> -13.535406 * E(expt): 13.604 1267.19 16.3557=> -13.604021 * * ------------------------------ * att0: (380.272453-202.552042)/200.000000 = 0.888602 * att1: (46.724263-1.351243)/49.000000 = 0.925980 * att2: (596.186722-112.604149)/600.000000 = 0.805971 * att3: (0.996650-0.010689)/0.995000 = 0.990915 * att4: (49.936395-1.547568)/50.000000 = 0.967777 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 71 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 **************************************************************** * * 71 points. Chose rsnum 40 (thus using 31 points) * Of 355 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.2817 * base 205.94 46.305 596.759 0.132333 29.483 * experiment 292.15 49.4385 573.514 0.393933 9.88583 * est rs center 270.695 24.264 496.425 0.463842 22.8663 * est rs spread 42.6932 14.3642 61.6693 0.292363 13.0291 * * Newtiness: 0.000000 * E(rec): 528.522 29850.7 23.7599=> -528.522300 * E(expt): 667.929 36257.1 8.75775=> -667.928917 * * ------------------------------ * att0: (379.576895-202.006953)/200.000000 = 0.887850 * att1: (49.435246-1.431876)/49.000000 = 0.979661 * att2: (597.502133-372.193962)/600.000000 = 0.375514 * att3: (0.992137-0.018570)/0.995000 = 0.978459 * att4: (49.400585-0.257539)/50.000000 = 0.982861 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 72 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 **************************************************************** * * 72 points. Chose rsnum 44 (thus using 28 points) * Of 618 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.1618 * base 200.517 34.7607 570.605 0.0051615 48.694 * experiment 389.095 46.4268 575.093 0.860485 8.11939 * est rs center 258.81 28.8659 509.011 0.450818 22.1217 * est rs spread 41.2077 14.5261 56.1596 0.270605 13.5953 * * Newtiness: 0.603158 * E(rec): -50.0125 -9246.74 9.3946=> 50.012507 * E(expt): -600.976 -29561.2 40.2751=> 600.975586 * * ------------------------------ * att0: (365.815320-200.132497)/200.000000 = 0.828414 * att1: (49.922244-1.248248)/49.000000 = 0.993347 * att2: (599.979182-408.588241)/600.000000 = 0.318985 * att3: (0.995482-0.010125)/0.995000 = 0.990309 * att4: (48.860403-0.093764)/50.000000 = 0.975333 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 73 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 **************************************************************** * * 73 points. Chose rsnum 45 (thus using 28 points) * Of 687 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.1456 * base 200.517 34.7607 570.605 0.0051615 48.694 * experiment 232.34 34.8154 571.286 0.639857 20.1512 * est rs center 261.195 28.99 521.738 0.479942 19.5107 * est rs spread 42.9546 12.982 52.7532 0.280768 13.9975 * * Newtiness: 0.000000 * E(rec): -50.0125 -9246.74 9.3946=> 50.012507 * E(expt): -159.003 -11943.4 1.6101=> 159.002941 * * ------------------------------ * att0: (372.876720-200.381125)/200.000000 = 0.862478 * att1: (49.699291-1.065184)/49.000000 = 0.992533 * att2: (599.750800-406.324035)/600.000000 = 0.322378 * att3: (0.995572-0.005888)/0.995000 = 0.994657 * att4: (49.573119-0.317013)/50.000000 = 0.985122 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 74 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 **************************************************************** * * 74 points. Chose rsnum 28 (thus using 46 points) * Of 305 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3279 * base 200 30.8223 550.912 0.005 47.0576 * experiment 200.072 30.9104 542.269 0.0335058 46.9859 * est rs center 276.357 27.5362 459.617 0.460679 18.6311 * est rs spread 48.4028 12.8579 94.4923 0.253889 13.5142 * * Newtiness: 0.332729 * E(rec): 22.4622 2048.04 7.48521=> -22.462201 * E(expt): 21.2262 1826.29 7.28005=> -21.226179 * * ------------------------------ * att0: (390.278460-200.883130)/200.000000 = 0.946977 * att1: (48.279711-2.089801)/49.000000 = 0.942651 * att2: (596.618422-261.800275)/600.000000 = 0.558030 * att3: (0.954285-0.009007)/0.995000 = 0.950028 * att4: (49.229864-0.772219)/50.000000 = 0.969153 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 75 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 **************************************************************** * * 75 points. Chose rsnum 29 (thus using 46 points) * Of 293 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3413 * base 200 28.3241 538.096 0.005 39.2158 * experiment 204.055 28.4145 540.47 0.0100279 38.6097 * est rs center 265.087 26.4309 440.094 0.494548 19.9475 * est rs spread 47.3015 13.2759 94.6822 0.298319 12.8883 * * Newtiness: 0.230384 * E(rec): 23.1823 2078 5.48604=> -23.182279 * E(expt): 23.5535 2097.39 5.3425=> -23.553454 * * ------------------------------ * att0: (382.346024-200.871277)/200.000000 = 0.907374 * att1: (49.397781-1.769587)/49.000000 = 0.972004 * att2: (594.467853-224.649840)/600.000000 = 0.616363 * att3: (0.983844-0.007802)/0.995000 = 0.980947 * att4: (49.753503-0.018111)/50.000000 = 0.994708 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 76 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 **************************************************************** * * 76 points. Chose rsnum 26 (thus using 50 points) * Of 283 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3534 * base 200 27.4388 590.656 0.005 43.8535 * experiment 204.754 6.79521 257.242 0.58918 1.36583 * est rs center 276.811 27.5866 452.668 0.487669 21.8242 * est rs spread 51.8472 13.4442 98.7689 0.303484 12.9334 * * Newtiness: 0.000000 * E(rec): 58.2637 6249.82 11.4906=> -58.263684 * E(expt): 26.2537 2319.4 3.53117=> -26.253717 * * ------------------------------ * att0: (388.216293-201.328392)/200.000000 = 0.934440 * att1: (48.116413-2.163862)/49.000000 = 0.937807 * att2: (599.981415-220.758926)/600.000000 = 0.632037 * att3: (0.981970-0.008259)/0.995000 = 0.978604 * att4: (48.597347-0.516979)/50.000000 = 0.961607 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 77 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 **************************************************************** * * 77 points. Chose rsnum 27 (thus using 50 points) * Of 253 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3953 * base 200 26.6862 600 0.005 43.6946 * experiment 332.893 49.2979 518.465 0.429241 48.6066 * est rs center 274.316 27.5036 458.947 0.535006 21.8882 * est rs spread 48.9132 14.6267 102.322 0.274387 15.0599 * * Newtiness: 0.000000 * E(rec): 43.5173 2783.18 5.08572=> -43.517290 * E(expt): 132.904 12683.5 5.59753=> -132.903585 * * ------------------------------ * att0: (392.180927-200.832633)/200.000000 = 0.956741 * att1: (49.787677-1.215906)/49.000000 = 0.991261 * att2: (598.019833-256.233646)/600.000000 = 0.569644 * att3: (0.986150-0.037633)/0.995000 = 0.953283 * att4: (49.225740-0.066986)/50.000000 = 0.983175 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 78 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 **************************************************************** * * 78 points. Chose rsnum 32 (thus using 46 points) * Of 303 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3300 * base 200 27.225 529.413 0.005 35.1949 * experiment 202.544 27.0001 527.359 0.0201118 35.4535 * est rs center 277.699 26.9025 454.004 0.462136 17.4611 * est rs spread 46.3051 14.6037 90.8949 0.296733 11.3198 * * Newtiness: 0.476013 * E(rec): 29.0382 2028.89 2.54924=> -29.038217 * E(expt): 28.4432 1930.45 2.45525=> -28.443234 * * ------------------------------ * att0: (382.180889-200.859922)/200.000000 = 0.906605 * att1: (49.587387-1.545923)/49.000000 = 0.980438 * att2: (599.678618-256.786163)/600.000000 = 0.571487 * att3: (0.955707-0.006048)/0.995000 = 0.954431 * att4: (46.385523-0.640721)/50.000000 = 0.914896 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 79 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 **************************************************************** * * 79 points. Chose rsnum 24 (thus using 55 points) * Of 207 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.4831 * base 200 30.884 600 0.005 50 * experiment 244.697 43.0067 559.136 0.37046 46.879 * est rs center 279.565 25.7072 418.453 0.469186 21.7012 * est rs spread 52.5811 13.8844 117.218 0.298634 13.3897 * * Newtiness: 0.000000 * E(rec): 8.92733 1483.48 2.80495=> -8.927329 * E(expt): 28.5603 2629.13 0.595961=> -28.560310 * * ------------------------------ * att0: (398.624786-201.168280)/200.000000 = 0.987283 * att1: (48.696289-1.852131)/49.000000 = 0.956003 * att2: (594.616285-73.126827)/600.000000 = 0.869149 * att3: (0.985786-0.036645)/0.995000 = 0.953911 * att4: (49.559940-0.430794)/50.000000 = 0.982583 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 80 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 **************************************************************** * * 80 points. Chose rsnum 25 (thus using 55 points) * Of 212 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.4717 * base 200 28.8777 600 0.005 48.84 * experiment 205.517 28.3276 590.813 0.0206317 48.9816 * est rs center 279.162 23.0228 440.572 0.436854 23.2921 * est rs spread 51.535 13.2197 108.443 0.292882 14.1349 * * Newtiness: 0.274283 * E(rec): 18.3587 1308.55 2.65402=> -18.358656 * E(expt): 20.914 1574.66 2.35031=> -20.913987 * * ------------------------------ * att0: (395.998327-201.029288)/200.000000 = 0.974845 * att1: (49.722136-1.385628)/49.000000 = 0.986459 * att2: (599.482565-230.062257)/600.000000 = 0.615701 * att3: (0.994732-0.023532)/0.995000 = 0.976081 * att4: (49.009155-0.384974)/50.000000 = 0.972484 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 81 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 **************************************************************** * * 81 points. Chose rsnum 31 (thus using 50 points) * Of 303 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3300 * base 200 26.236 531.007 0.005 30.2187 * experiment 204.874 26.7373 526.039 0.0107851 30.1792 * est rs center 279.302 25.2775 453.759 0.507268 19.9579 * est rs spread 50.3928 13.9938 95.8154 0.293608 13.2163 * * Newtiness: 0.900758 * E(rec): 33.9298 2343.86 2.29681=> -33.929826 * E(expt): 33.699 2285.42 2.15002=> -33.698956 * * ------------------------------ * att0: (394.513536-201.575486)/200.000000 = 0.964690 * att1: (49.683150-1.107361)/49.000000 = 0.991343 * att2: (597.071504-256.818267)/600.000000 = 0.567089 * att3: (0.986849-0.015728)/0.995000 = 0.976001 * att4: (47.514492-0.012758)/50.000000 = 0.950035 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 82 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 **************************************************************** * * 82 points. Chose rsnum 32 (thus using 50 points) * Of 292 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3425 * base 200 26.5009 546.12 0.005 32.2738 * experiment 200.879 26.8724 541.385 0.00821501 32.6692 * est rs center 271.798 26.3642 466.983 0.522453 21.0353 * est rs spread 50.3213 12.1774 88.1094 0.273981 14.3728 * * Newtiness: 0.388772 * E(rec): 38.6199 3563.77 2.83966=> -38.619941 * E(expt): 38.2898 3527.14 2.83016=> -38.289786 * * ------------------------------ * att0: (390.352581-202.303343)/200.000000 = 0.940246 * att1: (49.615365-2.300510)/49.000000 = 0.965609 * att2: (599.909186-274.806225)/600.000000 = 0.541838 * att3: (0.987431-0.018846)/0.995000 = 0.973452 * att4: (48.915505-0.463320)/50.000000 = 0.969044 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 83 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 **************************************************************** * * 83 points. Chose rsnum 28 (thus using 55 points) * Of 235 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.4255 * base 200 25.4538 600 0.005 42.1309 * experiment 306.153 28.0112 432.911 0.597539 29.9475 * est rs center 274.665 27.7313 446.958 0.461436 21.3855 * est rs spread 49.7244 13.3987 96.745 0.298913 14.3612 * * Newtiness: 0.000000 * E(rec): 44.9459 1723.31 2.13561=> -44.945902 * E(expt): 79.4962 6125.65 0.174975=> -79.496198 * * ------------------------------ * att0: (396.194353-202.324918)/200.000000 = 0.969347 * att1: (49.472780-1.264454)/49.000000 = 0.983843 * att2: (598.416590-265.014777)/600.000000 = 0.555670 * att3: (0.984575-0.007265)/0.995000 = 0.982220 * att4: (49.751340-0.342229)/50.000000 = 0.988182 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 84 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 306.1528 28.0112 432.9108 0.5975 29.9475 -> 22.0300 1121.4770 0.2869 **************************************************************** * * 84 points. Chose rsnum 29 (thus using 55 points) * Of 257 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3891 * base 200 24.9444 527.18 0.005 33.1722 * experiment 203.894 24.9113 519.507 0.00721546 32.4277 * est rs center 275.645 27.6605 452.092 0.505041 19.6846 * est rs spread 50.994 13.41 97.3901 0.295905 14.7429 * * Newtiness: 0.057144 * E(rec): 18.6201 -175.897 2.58318=> -18.620079 * E(expt): 18.395 -176.953 2.35675=> -18.395034 * * ------------------------------ * att0: (394.946506-203.092124)/200.000000 = 0.959272 * att1: (49.893668-1.705769)/49.000000 = 0.983427 * att2: (599.457604-255.413689)/600.000000 = 0.573407 * att3: (0.999015-0.009850)/0.995000 = 0.994135 * att4: (49.174489-0.206133)/50.000000 = 0.979367 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 85 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 306.1528 28.0112 432.9108 0.5975 29.9475 -> 22.0300 1121.4770 0.2869 203.8937 24.9113 519.5067 0.0072 32.4277 -> 1.6200 2.8280 0.2392 **************************************************************** * * 85 points. Chose rsnum 30 (thus using 55 points) * Of 332 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3012 * base 200 25.5471 544.014 0.005 35.9685 * experiment 296.071 13.8189 285.82 0.0593213 4.79293 * est rs center 270.542 22.7744 463.629 0.469643 21.1453 * est rs spread 48.349 14.1742 88.1448 0.296 13.1052 * * Newtiness: 0.000000 * E(rec): 12.9241 384.839 3.82952=> -12.924057 * E(expt): 26.8372 1739.96 1.58637=> -26.837237 * * ------------------------------ * att0: (380.133566-200.608452)/200.000000 = 0.897626 * att1: (49.315780-1.468799)/49.000000 = 0.976469 * att2: (599.477053-264.193082)/600.000000 = 0.558807 * att3: (0.999614-0.016526)/0.995000 = 0.988028 * att4: (49.574218-0.007598)/50.000000 = 0.991332 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 86 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 306.1528 28.0112 432.9108 0.5975 29.9475 -> 22.0300 1121.4770 0.2869 203.8937 24.9113 519.5067 0.0072 32.4277 -> 1.6200 2.8280 0.2392 296.0708 13.8189 285.8200 0.0593 4.7929 -> 40.0600 2714.5560 0.6679 **************************************************************** * * 86 points. Chose rsnum 31 (thus using 55 points) * Of 292 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3425 * base 200 25.5471 544.014 0.005 35.9685 * experiment 204.511 25.1545 545.88 0.0212882 35.9652 * est rs center 275.939 26.6884 461.528 0.484353 20.1057 * est rs spread 53.3277 12.8752 87.3632 0.277285 12.2878 * * Newtiness: 0.854522 * E(rec): 12.9241 384.839 3.82952=> -12.924057 * E(expt): 13.0338 328.834 3.67361=> -13.033816 * * ------------------------------ * att0: (395.581543-200.937418)/200.000000 = 0.973221 * att1: (49.862965-3.084920)/49.000000 = 0.954654 * att2: (597.849923-256.584702)/600.000000 = 0.568775 * att3: (0.996812-0.013131)/0.995000 = 0.988624 * att4: (48.256547-0.607363)/50.000000 = 0.952984 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 87 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 306.1528 28.0112 432.9108 0.5975 29.9475 -> 22.0300 1121.4770 0.2869 203.8937 24.9113 519.5067 0.0072 32.4277 -> 1.6200 2.8280 0.2392 296.0708 13.8189 285.8200 0.0593 4.7929 -> 40.0600 2714.5560 0.6679 204.5113 25.1545 545.8800 0.0213 35.9652 -> 8.8200 655.1860 0.3378 **************************************************************** * * 87 points. Chose rsnum 32 (thus using 55 points) * Of 354 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.2825 * base 200 26.3422 568.409 0.005 40.8328 * experiment 205.343 26.0453 576.09 0.0207915 40.5189 * est rs center 278.424 25.403 488.552 0.502466 21.0626 * est rs spread 55.7781 13.7528 86.0833 0.297482 13.0839 * * Newtiness: 0.502959 * E(rec): 7.58303 -233.412 4.44097=> -7.583029 * E(expt): 7.81042 -278.762 4.32182=> -7.810422 * * ------------------------------ * att0: (394.321923-200.894661)/200.000000 = 0.967136 * att1: (49.586993-1.753094)/49.000000 = 0.976202 * att2: (599.822013-281.173151)/600.000000 = 0.531081 * att3: (0.984863-0.006267)/0.995000 = 0.983514 * att4: (48.722220-0.028657)/50.000000 = 0.973871 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 88 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 306.1528 28.0112 432.9108 0.5975 29.9475 -> 22.0300 1121.4770 0.2869 203.8937 24.9113 519.5067 0.0072 32.4277 -> 1.6200 2.8280 0.2392 296.0708 13.8189 285.8200 0.0593 4.7929 -> 40.0600 2714.5560 0.6679 204.5113 25.1545 545.8800 0.0213 35.9652 -> 8.8200 655.1860 0.3378 205.3428 26.0453 576.0895 0.0208 40.5189 -> 0.5300 0.6930 0.2634 **************************************************************** * * 88 points. Chose rsnum 33 (thus using 55 points) * Of 331 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3021 * base 200 26.2589 559.212 0.005 39.9789 * experiment 216.025 3.93557 381.741 0.656518 27.9888 * est rs center 270.328 27.7734 472.237 0.482562 19.5 * est rs spread 50.9096 13.5458 85.6591 0.300692 13.8894 * * Newtiness: 0.000000 * E(rec): 4.86773 111.05 5.21009=> -4.867728 * E(expt): 15.6695 252.136 3.9505=> -15.669476 * * ------------------------------ * att0: (393.092939-200.060117)/200.000000 = 0.965164 * att1: (49.778993-1.504749)/49.000000 = 0.985189 * att2: (599.332907-262.820067)/600.000000 = 0.560855 * att3: (0.986747-0.029239)/0.995000 = 0.962320 * att4: (49.606637-0.423848)/50.000000 = 0.983656 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 89 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 306.1528 28.0112 432.9108 0.5975 29.9475 -> 22.0300 1121.4770 0.2869 203.8937 24.9113 519.5067 0.0072 32.4277 -> 1.6200 2.8280 0.2392 296.0708 13.8189 285.8200 0.0593 4.7929 -> 40.0600 2714.5560 0.6679 204.5113 25.1545 545.8800 0.0213 35.9652 -> 8.8200 655.1860 0.3378 205.3428 26.0453 576.0895 0.0208 40.5189 -> 0.5300 0.6930 0.2634 216.0246 3.9356 381.7411 0.6565 27.9888 -> 19.5800 491.5060 0.8490 **************************************************************** * * 89 points. Chose rsnum 29 (thus using 60 points) * Of 237 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.4219 * base 200 26.5769 600 0.005 44.7944 * experiment 201.267 27.2478 598.454 0.0207929 44.155 * est rs center 280.141 25.1556 455.694 0.451193 21.3115 * est rs spread 50.307 14.9918 88.031 0.282584 11.8889 * * Newtiness: 0.292874 * E(rec): 41.4827 2979.23 5.99913=> -41.482658 * E(expt): 41.8993 2967.45 5.85223=> -41.899260 * * ------------------------------ * att0: (381.237921-200.105955)/200.000000 = 0.905660 * att1: (49.814265-2.592121)/49.000000 = 0.963717 * att2: (599.630558-257.772818)/600.000000 = 0.569763 * att3: (0.955369-0.008584)/0.995000 = 0.951543 * att4: (47.133851-1.364226)/50.000000 = 0.915392 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 90 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 306.1528 28.0112 432.9108 0.5975 29.9475 -> 22.0300 1121.4770 0.2869 203.8937 24.9113 519.5067 0.0072 32.4277 -> 1.6200 2.8280 0.2392 296.0708 13.8189 285.8200 0.0593 4.7929 -> 40.0600 2714.5560 0.6679 204.5113 25.1545 545.8800 0.0213 35.9652 -> 8.8200 655.1860 0.3378 205.3428 26.0453 576.0895 0.0208 40.5189 -> 0.5300 0.6930 0.2634 216.0246 3.9356 381.7411 0.6565 27.9888 -> 19.5800 491.5060 0.8490 201.2670 27.2478 598.4537 0.0208 44.1550 -> 0.6100 0.9450 0.2636 **************************************************************** * * 90 points. Chose rsnum 30 (thus using 60 points) * Of 283 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3534 * base 200 26.5966 558.929 0.005 39.2052 * experiment 202.663 26.4405 559.167 0.016117 39.7131 * est rs center 280.569 25.8237 454.673 0.557848 19.5493 * est rs spread 46.1355 13.1821 99.6278 0.294936 13.4934 * * Newtiness: 0.946773 * E(rec): 15.0645 -570.951 3.37636=> -15.064533 * E(expt): 15.1478 -617.587 3.34289=> -15.147769 * * ------------------------------ * att0: (380.284493-201.226148)/200.000000 = 0.895292 * att1: (49.238984-1.240121)/49.000000 = 0.979569 * att2: (599.328338-276.370868)/600.000000 = 0.538262 * att3: (0.978565-0.020059)/0.995000 = 0.963322 * att4: (49.688267-0.075868)/50.000000 = 0.992248 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 91 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 306.1528 28.0112 432.9108 0.5975 29.9475 -> 22.0300 1121.4770 0.2869 203.8937 24.9113 519.5067 0.0072 32.4277 -> 1.6200 2.8280 0.2392 296.0708 13.8189 285.8200 0.0593 4.7929 -> 40.0600 2714.5560 0.6679 204.5113 25.1545 545.8800 0.0213 35.9652 -> 8.8200 655.1860 0.3378 205.3428 26.0453 576.0895 0.0208 40.5189 -> 0.5300 0.6930 0.2634 216.0246 3.9356 381.7411 0.6565 27.9888 -> 19.5800 491.5060 0.8490 201.2670 27.2478 598.4537 0.0208 44.1550 -> 0.6100 0.9450 0.2636 202.6634 26.4405 559.1671 0.0161 39.7131 -> 0.8400 1.6820 0.2480 **************************************************************** * * 91 points. Chose rsnum 50 (thus using 41 points) * Of 488 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.2049 * base 205.517 28.3276 590.813 0.0206317 48.9816 * experiment 393.749 19.2252 593.325 0.790778 13.8667 * est rs center 268.527 26.2346 531.03 0.527017 22.1779 * est rs spread 45.8566 14.0835 43.1457 0.263675 13.642 * * Newtiness: 0.000000 * E(rec): -394.295 -30678.7 -2.2706=> 394.295359 * E(expt): -685.084 -45629.5 13.5191=> 685.083807 * * ------------------------------ * att0: (383.482622-200.352074)/200.000000 = 0.915653 * att1: (49.010647-1.293467)/49.000000 = 0.973820 * att2: (599.236344-435.151581)/600.000000 = 0.273475 * att3: (0.987275-0.013326)/0.995000 = 0.978844 * att4: (47.862983-0.195628)/50.000000 = 0.953347 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 92 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 306.1528 28.0112 432.9108 0.5975 29.9475 -> 22.0300 1121.4770 0.2869 203.8937 24.9113 519.5067 0.0072 32.4277 -> 1.6200 2.8280 0.2392 296.0708 13.8189 285.8200 0.0593 4.7929 -> 40.0600 2714.5560 0.6679 204.5113 25.1545 545.8800 0.0213 35.9652 -> 8.8200 655.1860 0.3378 205.3428 26.0453 576.0895 0.0208 40.5189 -> 0.5300 0.6930 0.2634 216.0246 3.9356 381.7411 0.6565 27.9888 -> 19.5800 491.5060 0.8490 201.2670 27.2478 598.4537 0.0208 44.1550 -> 0.6100 0.9450 0.2636 202.6634 26.4405 559.1671 0.0161 39.7131 -> 0.8400 1.6820 0.2480 393.7486 19.2252 593.3251 0.7908 13.8667 -> 2.2800 6.4740 0.5592 **************************************************************** * * 92 points. Chose rsnum 32 (thus using 60 points) * Of 347 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.2882 * base 200 27.5934 600 0.005 44.2991 * experiment 201.268 27.447 596.059 0.0257903 45.0234 * est rs center 275.503 25.6058 481.47 0.517032 16.5354 * est rs spread 55.3528 13.4278 88.0048 0.304407 11.955 * * Newtiness: 0.096924 * E(rec): -1.65214 -271.666 5.82672=> 1.652138 * E(expt): -2.04506 -379.775 5.8152=> 2.045065 * * ------------------------------ * att0: (397.933816-200.993825)/200.000000 = 0.984700 * att1: (49.627626-1.379019)/49.000000 = 0.984665 * att2: (599.603879-282.157304)/600.000000 = 0.529078 * att3: (0.997034-0.005214)/0.995000 = 0.996804 * att4: (48.595061-0.175458)/50.000000 = 0.968392 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 93 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 306.1528 28.0112 432.9108 0.5975 29.9475 -> 22.0300 1121.4770 0.2869 203.8937 24.9113 519.5067 0.0072 32.4277 -> 1.6200 2.8280 0.2392 296.0708 13.8189 285.8200 0.0593 4.7929 -> 40.0600 2714.5560 0.6679 204.5113 25.1545 545.8800 0.0213 35.9652 -> 8.8200 655.1860 0.3378 205.3428 26.0453 576.0895 0.0208 40.5189 -> 0.5300 0.6930 0.2634 216.0246 3.9356 381.7411 0.6565 27.9888 -> 19.5800 491.5060 0.8490 201.2670 27.2478 598.4537 0.0208 44.1550 -> 0.6100 0.9450 0.2636 202.6634 26.4405 559.1671 0.0161 39.7131 -> 0.8400 1.6820 0.2480 393.7486 19.2252 593.3251 0.7908 13.8667 -> 2.2800 6.4740 0.5592 201.2680 27.4470 596.0589 0.0258 45.0234 -> 9.5200 817.5140 0.3011 **************************************************************** * * 93 points. Chose rsnum 33 (thus using 60 points) * Of 381 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.2625 * base 200 25.1265 486.497 0.005 25.3421 * experiment 201.596 25.2952 491.928 0.0216595 24.6541 * est rs center 285.417 23.6151 472.62 0.482533 17.9087 * est rs spread 55.6889 13.0492 89.824 0.279524 11.6619 * * Newtiness: 0.131573 * E(rec): 0.44028 174.379 2.4368=> -0.440280 * E(expt): 0.58115 165.412 2.45396=> -0.581150 * * ------------------------------ * att0: (397.895049-200.442659)/200.000000 = 0.987262 * att1: (49.996544-1.341106)/49.000000 = 0.992968 * att2: (597.368128-284.046236)/600.000000 = 0.522203 * att3: (0.998758-0.011938)/0.995000 = 0.991779 * att4: (47.210283-0.229926)/50.000000 = 0.939607 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 94 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 306.1528 28.0112 432.9108 0.5975 29.9475 -> 22.0300 1121.4770 0.2869 203.8937 24.9113 519.5067 0.0072 32.4277 -> 1.6200 2.8280 0.2392 296.0708 13.8189 285.8200 0.0593 4.7929 -> 40.0600 2714.5560 0.6679 204.5113 25.1545 545.8800 0.0213 35.9652 -> 8.8200 655.1860 0.3378 205.3428 26.0453 576.0895 0.0208 40.5189 -> 0.5300 0.6930 0.2634 216.0246 3.9356 381.7411 0.6565 27.9888 -> 19.5800 491.5060 0.8490 201.2670 27.2478 598.4537 0.0208 44.1550 -> 0.6100 0.9450 0.2636 202.6634 26.4405 559.1671 0.0161 39.7131 -> 0.8400 1.6820 0.2480 393.7486 19.2252 593.3251 0.7908 13.8667 -> 2.2800 6.4740 0.5592 201.2680 27.4470 596.0589 0.0258 45.0234 -> 9.5200 817.5140 0.3011 201.5957 25.2952 491.9284 0.0217 24.6541 -> 1.7500 3.2270 0.2939 **************************************************************** * * 94 points. Chose rsnum 34 (thus using 60 points) * Of 338 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.2959 * base 200 25.6928 493.356 0.005 26.6373 * experiment 205.894 25.0304 488.189 0.0193509 26.942 * est rs center 264.527 27.6245 480.893 0.507012 22.3979 * est rs spread 45.2033 12.8955 81.8152 0.287876 13.162 * * Newtiness: 0.846700 * E(rec): 0.813616 -52.5135 1.78234=> -0.813616 * E(expt): -0.350564 -132.941 1.67935=> 0.350564 * * ------------------------------ * att0: (369.344342-200.217715)/200.000000 = 0.845633 * att1: (49.612782-3.170369)/49.000000 = 0.947804 * att2: (598.559295-282.155059)/600.000000 = 0.527340 * att3: (0.970710-0.010575)/0.995000 = 0.964960 * att4: (48.742032-0.095508)/50.000000 = 0.972930 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 95 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 306.1528 28.0112 432.9108 0.5975 29.9475 -> 22.0300 1121.4770 0.2869 203.8937 24.9113 519.5067 0.0072 32.4277 -> 1.6200 2.8280 0.2392 296.0708 13.8189 285.8200 0.0593 4.7929 -> 40.0600 2714.5560 0.6679 204.5113 25.1545 545.8800 0.0213 35.9652 -> 8.8200 655.1860 0.3378 205.3428 26.0453 576.0895 0.0208 40.5189 -> 0.5300 0.6930 0.2634 216.0246 3.9356 381.7411 0.6565 27.9888 -> 19.5800 491.5060 0.8490 201.2670 27.2478 598.4537 0.0208 44.1550 -> 0.6100 0.9450 0.2636 202.6634 26.4405 559.1671 0.0161 39.7131 -> 0.8400 1.6820 0.2480 393.7486 19.2252 593.3251 0.7908 13.8667 -> 2.2800 6.4740 0.5592 201.2680 27.4470 596.0589 0.0258 45.0234 -> 9.5200 817.5140 0.3011 201.5957 25.2952 491.9284 0.0217 24.6541 -> 1.7500 3.2270 0.2939 205.8935 25.0304 488.1891 0.0194 26.9420 -> 2.0700 5.4310 0.4526 **************************************************************** * * 95 points. Chose rsnum 54 (thus using 41 points) * Of 606 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.1650 * base 200.072 30.9104 542.269 0.0335058 46.9859 * experiment 268.449 8.79951 431.749 0.056392 39.4709 * est rs center 254.369 24.6455 507.997 0.415623 20.4964 * est rs spread 35.4375 12.3177 57.0699 0.286011 12.2564 * * Newtiness: 0.000000 * E(rec): 214.513 8415.46 -14.9379=> -214.512576 * E(expt): -44.6606 -763.53 5.80562=> 44.660601 * * ------------------------------ * att0: (353.292979-202.486276)/200.000000 = 0.754034 * att1: (48.976865-1.261501)/49.000000 = 0.973783 * att2: (599.145817-406.231218)/600.000000 = 0.321524 * att3: (0.994728-0.018827)/0.995000 = 0.980805 * att4: (43.252359-0.138219)/50.000000 = 0.862283 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 96 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 306.1528 28.0112 432.9108 0.5975 29.9475 -> 22.0300 1121.4770 0.2869 203.8937 24.9113 519.5067 0.0072 32.4277 -> 1.6200 2.8280 0.2392 296.0708 13.8189 285.8200 0.0593 4.7929 -> 40.0600 2714.5560 0.6679 204.5113 25.1545 545.8800 0.0213 35.9652 -> 8.8200 655.1860 0.3378 205.3428 26.0453 576.0895 0.0208 40.5189 -> 0.5300 0.6930 0.2634 216.0246 3.9356 381.7411 0.6565 27.9888 -> 19.5800 491.5060 0.8490 201.2670 27.2478 598.4537 0.0208 44.1550 -> 0.6100 0.9450 0.2636 202.6634 26.4405 559.1671 0.0161 39.7131 -> 0.8400 1.6820 0.2480 393.7486 19.2252 593.3251 0.7908 13.8667 -> 2.2800 6.4740 0.5592 201.2680 27.4470 596.0589 0.0258 45.0234 -> 9.5200 817.5140 0.3011 201.5957 25.2952 491.9284 0.0217 24.6541 -> 1.7500 3.2270 0.2939 205.8935 25.0304 488.1891 0.0194 26.9420 -> 2.0700 5.4310 0.4526 268.4486 8.7995 431.7488 0.0564 39.4709 -> 15.8600 675.6280 0.4936 **************************************************************** * * 96 points. Chose rsnum 36 (thus using 60 points) * Of 338 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.2959 * base 200 23.9443 483.364 0.005 25.2032 * experiment 205.969 23.6028 483.697 0.0226167 25.6153 * est rs center 275.947 27.0612 497.846 0.480304 17.9108 * est rs spread 53.09 13.3095 80.3257 0.30114 12.3178 * * Newtiness: 0.188475 * E(rec): -0.986718 210.191 1.5206=> 0.986718 * E(expt): -1.76706 132.977 1.43351=> 1.767059 * * ------------------------------ * att0: (399.674225-200.461916)/200.000000 = 0.996062 * att1: (49.909438-1.248295)/49.000000 = 0.993085 * att2: (598.904491-284.914134)/600.000000 = 0.523317 * att3: (0.989957-0.013213)/0.995000 = 0.981652 * att4: (44.026484-0.115897)/50.000000 = 0.878212 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 97 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 306.1528 28.0112 432.9108 0.5975 29.9475 -> 22.0300 1121.4770 0.2869 203.8937 24.9113 519.5067 0.0072 32.4277 -> 1.6200 2.8280 0.2392 296.0708 13.8189 285.8200 0.0593 4.7929 -> 40.0600 2714.5560 0.6679 204.5113 25.1545 545.8800 0.0213 35.9652 -> 8.8200 655.1860 0.3378 205.3428 26.0453 576.0895 0.0208 40.5189 -> 0.5300 0.6930 0.2634 216.0246 3.9356 381.7411 0.6565 27.9888 -> 19.5800 491.5060 0.8490 201.2670 27.2478 598.4537 0.0208 44.1550 -> 0.6100 0.9450 0.2636 202.6634 26.4405 559.1671 0.0161 39.7131 -> 0.8400 1.6820 0.2480 393.7486 19.2252 593.3251 0.7908 13.8667 -> 2.2800 6.4740 0.5592 201.2680 27.4470 596.0589 0.0258 45.0234 -> 9.5200 817.5140 0.3011 201.5957 25.2952 491.9284 0.0217 24.6541 -> 1.7500 3.2270 0.2939 205.8935 25.0304 488.1891 0.0194 26.9420 -> 2.0700 5.4310 0.4526 268.4486 8.7995 431.7488 0.0564 39.4709 -> 15.8600 675.6280 0.4936 205.9690 23.6028 483.6967 0.0226 25.6153 -> 5.2600 94.1240 0.3587 **************************************************************** * * 97 points. Chose rsnum 31 (thus using 66 points) * Of 290 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3448 * base 345.7 19.5097 600 1 0 * experiment 346.722 20.1373 583.567 0.987558 0.833884 * est rs center 284.854 27.685 472.083 0.489778 19.8485 * est rs spread 54.6348 14.0915 89.7425 0.291671 12.8747 * * Newtiness: 0.640672 * E(rec): -19.3632 -863.156 0.0159032=> 19.363238 * E(expt): -15.9631 -480.139 -0.00386479=> 15.963138 * * ------------------------------ * att0: (398.047523-200.145384)/200.000000 = 0.989511 * att1: (49.313544-1.324733)/49.000000 = 0.979363 * att2: (599.569906-281.386751)/600.000000 = 0.530305 * att3: (0.989309-0.007911)/0.995000 = 0.986330 * att4: (49.972545-0.007497)/50.000000 = 0.999301 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 98 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 306.1528 28.0112 432.9108 0.5975 29.9475 -> 22.0300 1121.4770 0.2869 203.8937 24.9113 519.5067 0.0072 32.4277 -> 1.6200 2.8280 0.2392 296.0708 13.8189 285.8200 0.0593 4.7929 -> 40.0600 2714.5560 0.6679 204.5113 25.1545 545.8800 0.0213 35.9652 -> 8.8200 655.1860 0.3378 205.3428 26.0453 576.0895 0.0208 40.5189 -> 0.5300 0.6930 0.2634 216.0246 3.9356 381.7411 0.6565 27.9888 -> 19.5800 491.5060 0.8490 201.2670 27.2478 598.4537 0.0208 44.1550 -> 0.6100 0.9450 0.2636 202.6634 26.4405 559.1671 0.0161 39.7131 -> 0.8400 1.6820 0.2480 393.7486 19.2252 593.3251 0.7908 13.8667 -> 2.2800 6.4740 0.5592 201.2680 27.4470 596.0589 0.0258 45.0234 -> 9.5200 817.5140 0.3011 201.5957 25.2952 491.9284 0.0217 24.6541 -> 1.7500 3.2270 0.2939 205.8935 25.0304 488.1891 0.0194 26.9420 -> 2.0700 5.4310 0.4526 268.4486 8.7995 431.7488 0.0564 39.4709 -> 15.8600 675.6280 0.4936 205.9690 23.6028 483.6967 0.0226 25.6153 -> 5.2600 94.1240 0.3587 346.7224 20.1373 583.5674 0.9876 0.8339 -> 2.3600 6.0740 1.8412 **************************************************************** * * 98 points. Chose rsnum 32 (thus using 66 points) * Of 371 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.2695 * base 344.619 20.6252 600 1 0 * experiment 346.319 19.9473 590.629 0.984561 0.0338217 * est rs center 276.982 26.7358 460.537 0.464342 19.3798 * est rs spread 53.6346 14.4229 89.1099 0.281673 11.1441 * * Newtiness: 0.485706 * E(rec): -30.4997 -1450.31 0.593598=> 30.499711 * E(expt): -29.5807 -1314.82 0.468503=> 29.580715 * * ------------------------------ * att0: (392.631260-200.275083)/200.000000 = 0.961781 * att1: (49.917546-1.624109)/49.000000 = 0.985580 * att2: (593.219444-286.342702)/600.000000 = 0.511461 * att3: (0.983920-0.014220)/0.995000 = 0.974572 * att4: (46.218699-1.099409)/50.000000 = 0.902386 * *************************************************************** A dataset with the following dimensions: Number of inputs = 5 Number of outputs = 3 Number of datapoints = 99 Input 0 called attribute0 range: 200 to 400 Input 1 called attribute1 range: 0 to 50 Input 2 called attribute2 range: 0 to 600 Input 3 called attribute3 range: 0 to 1 Input 4 called attribute4 range: 0 to 50 Output 0 called output0 range: 0 to 120 Output 1 called output1 range: 0 to 16000 Output 2 called output2 range: 0 to 4 394.2555 43.1513 352.8510 0.1846 48.8325 -> 57.5100 5640.7090 0.3045 309.1847 4.6646 357.1789 0.9710 10.1891 -> 48.5600 3825.1180 1.0361 209.9723 37.1164 18.6024 0.7619 37.8684 -> 50.5800 2883.8460 0.2505 390.0062 24.4780 204.6618 0.1316 12.7733 -> 78.2700 8639.9590 0.5504 394.2807 48.6348 82.6644 0.9398 24.2781 -> 105.7500 13512.4850 0.4317 251.9097 6.2181 101.5364 0.0851 40.3065 -> 62.2800 4479.5160 0.2235 393.1486 3.3359 549.5100 0.4929 43.0287 -> 52.2200 6120.1680 0.7583 210.7786 27.0031 557.6104 0.6679 41.0007 -> 6.7200 75.5560 1.9259 325.2625 21.1426 219.8133 0.7352 45.5875 -> 75.9000 7597.7940 0.2249 254.1780 15.2090 3.8900 0.0773 2.8887 -> 84.4500 7932.3590 2.4813 267.5736 9.9478 532.4776 0.0296 4.2931 -> 4.3500 92.0430 0.8742 365.5440 42.3531 551.8719 0.6311 25.6141 -> 33.8400 3038.7100 0.2945 205.4449 49.3628 587.2551 0.0134 48.5061 -> 3.6300 15.0710 0.4113 204.2633 43.4142 541.3873 0.7999 6.7779 -> 6.8400 47.4200 0.3497 202.6723 1.7382 582.4674 0.9838 0.0067 -> 9.5600 362.3860 2.0533 290.3354 34.4914 190.0677 0.7064 0.5761 -> 71.7200 6278.7280 0.6735 385.1752 18.5293 33.5188 0.8814 11.2985 -> 104.5300 14001.0010 0.7839 205.7753 25.7313 301.5618 0.2441 18.6406 -> 9.3300 186.7650 0.3282 316.7625 43.5425 579.8736 0.9791 0.8255 -> 6.2800 69.9860 1.2012 375.0187 2.2912 312.0681 0.0274 40.8324 -> 61.4000 6125.4060 0.4811 203.1973 2.3056 16.7346 0.9984 49.7053 -> 51.4700 2897.9310 0.1647 399.3617 32.0546 596.4768 0.9947 0.7475 -> 3.5000 15.4760 2.0218 228.7222 6.6181 15.0531 0.9574 3.9426 -> 59.1300 4592.5750 1.3906 392.8394 1.5732 49.8528 0.1035 23.1365 -> 118.7500 15635.6810 0.4796 203.1925 23.2049 583.4117 0.0274 21.1055 -> 1.6000 2.9580 1.3510 314.3571 49.3846 63.2885 0.2972 42.3151 -> 90.5100 9621.4850 0.2860 380.6463 49.8280 201.1761 0.3954 9.4031 -> 69.6600 6440.6680 0.5708 247.3431 5.7023 397.9559 0.5278 49.1318 -> 23.0800 926.8400 0.6417 204.6188 49.4370 382.8799 0.9731 49.9484 -> 18.8200 459.3440 0.1543 204.8939 1.8394 588.6262 0.1421 0.1148 -> 11.9400 427.4380 2.6937 203.6825 9.2973 583.7655 0.0100 49.6652 -> 3.3000 10.9240 0.4186 399.1716 47.2600 593.5053 0.0308 1.0590 -> 38.0300 5168.2090 1.3901 205.4001 49.6588 221.5783 0.0327 48.9180 -> 26.1700 821.3810 0.1534 204.6193 15.0504 569.2812 0.2251 30.6426 -> 3.6500 21.6270 0.3198 376.2411 3.2224 325.1771 0.5582 8.6597 -> 45.2000 4578.0680 1.1732 203.1939 26.1716 435.0726 0.0348 48.7059 -> 6.4500 64.1670 0.2019 205.5460 2.1706 519.4595 0.0297 31.2049 -> 6.1100 111.6990 0.6445 201.5521 18.7809 591.4971 0.2876 22.5668 -> 1.4100 4.1890 0.4581 281.0012 45.3525 250.4850 0.1928 25.5239 -> 50.5900 3327.4590 0.3165 395.9568 8.9091 586.0883 0.3709 0.5000 -> 13.5700 395.1470 1.0759 200.4598 26.2194 484.1043 0.0110 49.5818 -> 0.7000 1.0860 0.1985 248.2996 43.0583 397.7994 0.2501 0.1081 -> 5.9500 38.4310 2.0674 214.4208 47.0541 253.2328 0.1874 28.3728 -> 21.4300 698.8070 0.2638 200.0557 36.1729 281.7484 0.4236 48.2204 -> 23.1100 678.4090 0.1465 203.1812 39.3625 446.4388 0.0142 48.7948 -> 3.3100 15.8590 0.1989 302.0588 30.2960 586.7629 0.1991 37.3792 -> 4.5400 112.7200 0.3073 296.9928 17.9238 582.3184 0.6948 1.3157 -> 7.5900 334.0690 0.9400 322.8008 6.7276 579.8852 0.0318 28.4740 -> 13.8900 522.1590 0.6585 267.9804 1.6461 342.6721 0.0886 20.5030 -> 19.3800 539.0680 1.4771 264.8169 15.9467 185.1214 0.9807 30.3817 -> 59.7500 4330.4210 0.4507 201.4636 36.1410 596.5154 0.2001 29.1826 -> 2.9500 9.2550 0.2162 204.3821 46.1719 409.3780 0.1456 10.8440 -> 8.2300 87.2030 0.3578 205.9401 46.3050 596.7589 0.1323 29.4830 -> 5.4300 30.0670 0.2360 204.0077 19.7683 392.4931 0.9339 15.2219 -> 1.3300 1.8430 0.5324 204.9637 2.9274 199.7920 0.3815 22.6107 -> 34.4900 1430.3250 0.9580 319.5229 28.2997 464.8505 0.2933 11.4258 -> 7.2500 195.4610 0.4458 200.6827 23.2865 374.6065 0.0100 0.4594 -> 3.4000 12.3040 1.4994 326.5390 14.9650 543.0423 0.9504 31.4343 -> 26.7400 1946.0060 0.3971 295.2123 24.7974 585.1468 0.3732 6.7099 -> 3.3000 10.9420 0.6500 255.1260 4.8001 598.3768 0.9169 22.4744 -> 15.7700 394.9090 0.7915 266.3021 21.3178 424.9011 0.3661 1.9331 -> 6.6500 226.9570 3.9012 347.0802 48.5486 592.9380 0.0303 0.1335 -> 19.6100 2482.9870 5.9072 282.3511 36.0714 588.8664 0.0131 23.3144 -> 4.1300 21.2930 0.3807 201.8085 29.3112 386.0755 0.9930 1.3727 -> 15.7800 1090.1840 1.4643 395.1488 24.0369 521.6686 0.0831 10.3300 -> 21.1000 1272.9180 0.4826 285.8149 47.7596 353.7917 0.7065 20.1181 -> 19.3200 904.8100 0.3201 279.3655 35.5011 588.9921 0.0145 23.6600 -> 7.9400 114.4880 0.2767 205.4883 23.9977 494.0753 0.1363 25.3711 -> 7.0300 77.0350 0.2635 204.9963 28.9681 550.7247 0.0092 44.0250 -> 0.7700 0.8330 0.3211 200.7744 26.0830 479.5637 0.0284 48.5650 -> 2.9900 12.0270 0.2034 200.5166 34.7607 570.6052 0.0052 48.6940 -> 3.1400 10.5320 0.2454 292.1503 49.4385 573.5139 0.3939 9.8858 -> 11.1000 196.8360 0.3702 389.0947 46.4268 575.0927 0.8605 8.1194 -> 6.9600 48.5440 0.4157 232.3396 34.8154 571.2859 0.6399 20.1512 -> 8.1300 118.9170 0.2705 200.0718 30.9104 542.2689 0.0335 46.9859 -> 1.0000 1.3300 0.2318 204.0549 28.4145 540.4700 0.0100 38.6097 -> 1.2300 1.7990 0.2211 204.7541 6.7952 257.2419 0.5892 1.3658 -> 3.9900 28.5190 1.0499 332.8931 49.2979 518.4647 0.4292 48.6066 -> 33.5900 2502.2270 0.1825 202.5436 27.0001 527.3586 0.0201 35.4535 -> 0.6200 0.6040 0.2553 244.6969 43.0067 559.1363 0.3705 46.8790 -> 14.8000 357.2860 0.1796 205.5173 28.3276 590.8135 0.0206 48.9816 -> 0.9700 1.9770 0.2870 204.8738 26.7373 526.0391 0.0108 30.1792 -> 1.7800 3.5340 0.3548 200.8785 26.8724 541.3850 0.0082 32.6692 -> 1.5800 2.7060 0.2798 306.1528 28.0112 432.9108 0.5975 29.9475 -> 22.0300 1121.4770 0.2869 203.8937 24.9113 519.5067 0.0072 32.4277 -> 1.6200 2.8280 0.2392 296.0708 13.8189 285.8200 0.0593 4.7929 -> 40.0600 2714.5560 0.6679 204.5113 25.1545 545.8800 0.0213 35.9652 -> 8.8200 655.1860 0.3378 205.3428 26.0453 576.0895 0.0208 40.5189 -> 0.5300 0.6930 0.2634 216.0246 3.9356 381.7411 0.6565 27.9888 -> 19.5800 491.5060 0.8490 201.2670 27.2478 598.4537 0.0208 44.1550 -> 0.6100 0.9450 0.2636 202.6634 26.4405 559.1671 0.0161 39.7131 -> 0.8400 1.6820 0.2480 393.7486 19.2252 593.3251 0.7908 13.8667 -> 2.2800 6.4740 0.5592 201.2680 27.4470 596.0589 0.0258 45.0234 -> 9.5200 817.5140 0.3011 201.5957 25.2952 491.9284 0.0217 24.6541 -> 1.7500 3.2270 0.2939 205.8935 25.0304 488.1891 0.0194 26.9420 -> 2.0700 5.4310 0.4526 268.4486 8.7995 431.7488 0.0564 39.4709 -> 15.8600 675.6280 0.4936 205.9690 23.6028 483.6967 0.0226 25.6153 -> 5.2600 94.1240 0.3587 346.7224 20.1373 583.5674 0.9876 0.8339 -> 2.3600 6.0740 1.8412 346.3191 19.9473 590.6285 0.9846 0.0338 -> 7.3500 282.8890 1.6417 **************************************************************** * * 99 points. Chose rsnum 33 (thus using 66 points) * Of 318 random points, 100 were inside rstat * Estimated rstat fractional volume is 0.3145 * base 200 27.2572 579.696 0.005 39.927 * experiment 203.262 46.0748 344.82 0.509954 14.2326 * est rs center 269.58 24.5637 478.596 0.488135 18.7664 * est rs spread 48.2791 13.2224 94.6508 0.287027 11.5366 * * Newtiness: 0.000000 * E(rec): 20.8594 1806.48 2.72776=> -20.859432 * E(expt): 33.112 1214.42 -0.173506=> -33.111990 * * ------------------------------ * att0: (397.186396-200.046632)/200.000000 = 0.985699 * att1: (49.199616-1.050512)/49.000000 = 0.982635 * att2: (598.213106-295.983105)/600.000000 = 0.503717 * att3: (0.989759-0.009462)/0.995000 = 0.985223 * att4: (48.603419-1.734810)/50.000000 = 0.937372 * ***************************************************************