- We present our equations in the
univariate setting. All results in the paper apply equally to the
- As described earlier, we
could also have selected queries by hillclimbing on
this low dimensional problem it was more computationally efficient to
consider a random candidate set.
- The times
reported are ``per reference point'' and ``per candidate per reference
point''; overall time must be computed from the number of candidates
and reference points examined. In the case of the LOESS model, for
example, with 100 training points, 64 reference points and 64
candidate points, the time required to select an action would be 194#194seconds, or about 0.3 seconds.
- It is worth mentioning that approximately half
of the training time for the mixture of Gaussians is spent computing
the correction factor in Equation 8. Without the
correction, the learner still computes 195#195, but does so by
modeling the training set distribution rather than the reference
distribution. We have found however, that for the problems examined,
the performance of such ``uncorrected'' learners does not differ
appreciably from that of the ``corrected'' learners.
Mon Mar 25 09:20:31 EST 1996