50 search results - page 3 / 10 » Learning Dynamic Naive Bayesian Classifiers |
ICML
2002
IEEE
15 years 11 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 ...
80
Voted
ICML
1999
IEEE
15 years 11 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...
100
Voted
AAAI
1996
14 years 11 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...
86
Voted
CORR
2000
Springer
14 years 10 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...
78
Voted
DIS
2004
Springer
15 years 2 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....