A Kolmogorov-Smirnoff Metric for Decision Tree Induction

Authors:
P. E. Utgoff;J. A. Clouse
Affiliations:
-;-
Venue:
A Kolmogorov-Smirnoff Metric for Decision Tree Induction
Year:
1996

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Abstract

In 1977, Friedman demonstrated that Kolmogorov-Smirnoff distance could be employed effectively as a test selection metric for decision tree induction. We revisit this metric and modify it to handle multiple classes within a single tree, and to be sensitive to missing data values. Empirical results for a large sample of learning tasks, comparing this metric to the gain ratio metric, show a highly significant reduction in tree size and expected number of tests for classification, without a significant change in classification accuracy.