50 search results - page 2 / 10 » Learning Dynamic Naive Bayesian Classifiers |
ICML
2001
IEEE
14 years 5 months ago
2001
IEEE
Accurate, well-calibrated estimates of class membership probabilities are needed in many supervised learning applications, in particular when a cost-sensitive decision must be mad...
JCIT
2010
12 years 11 months ago
2010
Probability theory is the framework for making decision under uncertainty. In classification, Bayes' rule is used to calculate the probabilities of the classes and it is a bi...
ICML
2003
IEEE
14 years 5 months ago
2003
IEEE
Bayesian classifiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent performance given their simplicity and heavy underlying independence assumptions....
ML
2000
ACM
13 years 4 months ago
2000
ACM
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...
ECML
2004
Springer
13 years 8 months ago
2004
Springer
It is well-known that naive Bayes performs surprisingly well in classification, but its probability estimation is poor. In many applications, however, a ranking based on class prob...