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...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy: Gámez Martín, José Antonio, Rumí, Rafael, Salmerón Cerdán, Antonio
Format: info:eu-repo/semantics/report
Język:English
Wydane: 2012
Dostęp online:http://hdl.handle.net/10835/1555