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ToolDiag: Feature selection software for improving classifiers.

ToolDiag is a feature selection program that increases the accuracy of classifiers and reduces their complexity by providing them with a subset containing only the most relevant features. It has interfaces to LVQ_PAK and SNNS, and uses a data file format that is compatible with that of LVQ_PAK. The 2-d graphics can be displayed using the GNUPLOT plotting package. ToolDiag implements many concepts from Devijver and Kittler's book "Pattern Recognition -- A Statistical Approach" (Prentice Hall, 1982), including the optimal branch and bound search strategy, together with several different selection criteria. ToolDiag can also perform an error estimation using the leave-one-out method and a K-nearest-neighbor classifier. It also includes a learning module (Q*) that has the same functionality as LVQ. ToolDiag cannot handle missing values and requires continuous or ordered discrete numerical features.

Version: 1.4.1 (3-DEC-93) Requires: C Ports: Test on IBM, DEC, NeXT, Sun, and DOS. Copying: Copyright (C) 1992, 1993 Thomas W. Rauber CD-ROM: Prime Time Freeware for AI, Issue 1-1 Author(s): Thomas Rauber Universidade Nova de Lisboa 2825 Monte Caparica PORTUGAL Tel: (+351) (1) 295-7787 Fax: (+351) (1) 295-7786 Keywords: Authors!Rauber, Branch and Bound Search, C!Code, Classification, Feature Selection, K Nearest Neighbor, Leave One Out, Machine Learning!Neural Networks, Neural Networks!Classification, ToolDiag References: ?
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