Class Summary |
ADNode |
The ADNode class implements the ADTree datastructure which increases
the speed with which sub-contingency tables can be constructed from
a data set in an Instances object. |
BayesNet |
Base class for a Bayes Network classifier. |
BayesNetB |
Class for a Bayes Network classifier based on a hill climbing algorithm for
learning structure as described in Buntine, W. |
BayesNetB2 |
Class for a Bayes Network classifier based on Buntines hill climbing algorithm for
learning structure, but augmented to allow arc reversal as an operation. |
BayesNetK2 |
Class for a Bayes Network classifier based on K2 for learning structure. |
DiscreteEstimatorBayes |
Symbolic probability estimator based on symbol counts and a prior. |
NaiveBayes |
Class for a Naive Bayes classifier using estimator classes. |
NaiveBayesSimple |
Class for building and using a simple Naive Bayes classifier. |
NaiveBayesSimpleSoft |
Version of NaiveBayesSimple that supports training on SoftClassifiedInstances
and WeightedInstances for use with SemiSupEM |
NaiveBayesUpdateable |
Class for a Naive Bayes classifier using estimator classes. |
ParentSet |
Helper class for Bayes Network classifiers. |
SemiSupEM |
Semi supervised learner that uses EM initialized with labeled data and then
runs EM iterations on the unlabeled data to improve the model. |
VaryNode |
Part of ADTree implementation. |