Implications of the Dirichlet Assumption for Discretization of Continuous Variables in Naive Bayesian Classifiers.

In a naive Bayesian classifier, discrete variables as well as discretized continuous variables are assumed to have Dirichlet priors. This paper describes the implications and applications of this model selection choice. We start by reviewing key properties of Dirichlet distributions. Among these pro...

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Bibliographic Details

Published in:	Machine learning. 53, 3 (2003).
Main Author:	Hsu, Chun-Nan
Format:	Article
Language:	English
Subjects:	Naive Bayesian classifiers. Dirichlet distributions. Perfect aggregation. Continuous variables. Discretization. Lazy discretization. Interval data.