A greedy algorithm for supervised discretization.

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.