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DIS
2004
Springer

Maximum a Posteriori Tree Augmented Naive Bayes Classifiers

14 years 4 months ago
Maximum a Posteriori Tree Augmented Naive Bayes Classifiers
Bayesian classifiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent performance given their simplicity and heavy underlying independence assumptions. In this paper we prove that under suitable conditions it is possible to calculate efficiently the maximum a posterior TAN model. Furthermore, we prove that it is also possible to calculate a weighted set with the k maximum a posteriori TAN models. This allows efficient TAN ensemble learning and accounting for model uncertainty. These results can be used to construct two classifiers.
Jesús Cerquides, Ramon López de M&aa
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2004
Where DIS
Authors Jesús Cerquides, Ramon López de Mántaras
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