50 search results - page 3 / 10 » Learning Dynamic Naive Bayesian Classifiers |
ICML
2002
IEEE
14 years 6 months ago
2002
IEEE
The naive classifier is a well-established mathematical model whose simplicity, speed and accuracy have made it a popular choice for classification in AI and engineering. In this ...
ICML
1999
IEEE
14 years 6 months ago
1999
IEEE
Lbr is a lazy semi-naive Bayesian classi er learning technique, designed to alleviate the attribute interdependence problem of naive Bayesian classi cation. To classify a test exa...
AAAI
1996
13 years 6 months ago
1996
Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competit...
CORR
2000
Springer
13 years 5 months ago
2000
Springer
We investigate the performance of two machine learning algorithms in the context of antispam filtering. The increasing volume of unsolicited bulk e-mail (spam) has generated a nee...
DIS
2004
Springer
13 years 9 months ago
2004
Springer
Bayesian classifiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent performance given their simplicity and heavy underlying independence assumptions....