32 search results - page 1 / 7 » Discretizing Continuous Attributes While Learning Bayesian N... |
ICML
1996
IEEE
14 years 5 months ago
1996
IEEE
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
ICML
1998
IEEE
14 years 5 months ago
1998
IEEE
In a recent paper, Friedman, Geiger, and Goldszmidt [8] introduced a classifier based on Bayesian networks, called Tree Augmented Naive Bayes (TAN), that outperforms naive Bayes a...
UAI
1998
13 years 6 months ago
1998
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...
ECML
1991
Springer
13 years 8 months ago
1991
Springer
1 A novel semi-naive Bayesian classifier is introduced that is particularly suitable to data with many attributes. The naive Bayesian classifier is taken as a starting point and co...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
AODE (Aggregating One-Dependence Estimators) is considered one of the most interesting representatives of the Bayesian classifiers, taking into account not only the low error rate...