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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Detalles Bibliográficos

Publicado en:	Machine learning. 53, 3 (2003).
Autor Principal:	Hsu, Chun-Nan
Formato:	Artigo
Idioma:	English
Subjects:	Naive Bayesian classifiers. Dirichlet distributions. Perfect aggregation. Continuous variables. Discretization. Lazy discretization. Interval data.