Abstract
The ability to restructure a decision tree efficiently enables a variety of approaches to decision tree induction that would otherwise be prohibitively expensive. Two such approaches are described here, one being incremental tree induction (ITI), and the other being non-incremental tree induction using a measure of tree quality instead of test quality (DMTI). These approaches and several variants offer new computational and classifier characteristics that lend themselves to particular applications.
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Utgoff, P.E., Berkman, N.C. & Clouse, J.A. Decision Tree Induction Based on Efficient Tree Restructuring. Machine Learning 29, 5–44 (1997). https://doi.org/10.1023/A:1007413323501
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DOI: https://doi.org/10.1023/A:1007413323501