Unsupervised naive Bayes for data clustering with mixtures of truncated exponentials

Unsupervised naive Bayes for data clustering with mixtures of truncated exponentials

In this paper we propose a naive Bayes model for unsupervised data clustering, where the class variable is hidden. The feature variables can be discrete or continuous, as the conditional distributions are represented as mixtures of truncated exponentials (MTEs). The number of classes is determined u...

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Dettagli Bibliografici
Autori principali:	Gámez Martín, José Antonio, Rumí, Rafael, Salmerón Cerdán, Antonio
Natura:	info:eu-repo/semantics/report
Lingua:	English
Pubblicazione:	2012
Accesso online:	http://hdl.handle.net/10835/1555

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