A greedy algorithm for supervised discretization

Authors:
Richard Butterworth;Dan A. Simovici;Gustavo S. Santos;Lucila Ohno-Machado
Affiliations:
Department of Computer Science, University of Massachusetts at Boston, Boston, MA;Department of Computer Science, University of Massachusetts at Boston, Boston, MA;Decision Systems Group, Division of Health Sciences and Technology, Harvard and MIT, Brigham and Womens' Hospital, 75 Francis Street, Boston, MA;Decision Systems Group, Division of Health Sciences and Technology, Harvard and MIT, Brigham and Womens' Hospital, 75 Francis Street, Boston, MA
Venue:
Journal of Biomedical Informatics - Special issue: Biomedical machine learning
Year:
2004

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Abstract

We present a greedy algorithm for supervised discretization using a metric defined on the space of partitions of a set of objects. This proposed technique is useful for preparing the data for classifiers that require nominal attributes. Experimental work on decision trees and naïve Bayes classifiers confirm the efficacy of the proposed algorithm.