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...
| Main Authors: | , , |
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| Format: | info:eu-repo/semantics/report |
| Language: | English |
| Published: |
2012
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| Online Access: | http://hdl.handle.net/10835/1555 |