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ICML
2003
IEEE
14 years 6 months ago
Tackling the Poor Assumptions of Naive Bayes Text Classifiers
Naive Bayes is often used as a baseline in text classification because it is fast and easy to implement. Its severe assumptions make such efficiency possible but also adversely af...
Jason D. Rennie, Lawrence Shih, Jaime Teevan, Davi...
ICML
2003
IEEE
14 years 6 months ago
Tractable Bayesian Learning of Tree Augmented Naive Bayes Models
Bayesian classifiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent performance given their simplicity and heavy underlying independence assumptions....
Jesús Cerquides, Ramon López de M&aa...
DIS
2004
Springer
13 years 9 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....
Jesús Cerquides, Ramon López de M&aa...
ICML
2005
IEEE
14 years 6 months ago
Augmenting naive Bayes for ranking
Naive Bayes is an effective and efficient learning algorithm in classification. In many applications, however, an accurate ranking of instances based on the class probability is m...
Harry Zhang, Liangxiao Jiang, Jiang Su
ECML
2006
Springer
13 years 9 months ago
Bayesian Learning of Markov Network Structure
Abstract. We propose a simple and efficient approach to building undirected probabilistic classification models (Markov networks) that extend na
Aleks Jakulin, Irina Rish