
Bayesian Network Classifier Toolbox
jBNC Toolkit
jBNC is a Java toolkit for training, testing,
and applying Bayesian Network Classifiers. Implemented classifiers
have been shown to perform well in a variety of artificial
intelligence, machine learning, and data mining applications.
Classifiers

Naive Bayes 

TAN  tree augmented naive Bayes 

FAN  forest augmented naive Bayes


STAN  selective tree augmented
naive Bayes 

STAND  selective tree augmented
naive Bayes with node discarding 

SFAN  selective forest augmented
naive Bayes 

STAND  selective forest augmented
naive Bayes with node discarding 
Network Quality Measures

HGC  HeckermanGeigerChickering 

SB  Standard Bayesian 

LC  Local criterion 

LOO  LeaveOneOut cross
validation 

CV_{n,t}  n
fold ttimes Cross Validation 
You can find an overview of jBNC Toolkit, including description how to use
tools contained in the tookit here.
Sample data can be downloaded here.
jBNCWEKA
jBNCWEKA package provides WEKA
bindings for jBNC. It allows running jBNC classifiers and utilities
from
within WEKA, in particular from WEKA's graphical user interface called
Explorer.
References

J.P. Sacha, L. Goodenday, and K.J. Cios.
"Bayesian learning for cardiac SPECT image interpretation", Artificial
Intelligence in Medicine, 26, pp.109143, 2002. 

J.P. Sacha. "New synthesis of Bayesian
network classifiers and interpretation of cardiac SPECT images", Ph.D. Dissertation, University of
Toledo, 1999. 

N. Friedman, D. Geiger, and M. Goldszmidt.
"Bayesian network classifiers", Machine
Learning, 29:2/3, 1997.

Related Links

applet.JavaBayes

Bayesian Networks in Java


GNU getopt  Java port


Weka  a collection of
machine learning algorithms in Java 

KDD 
data mining, knowledge discovery, genomic mining, and web mining
resources


UCI Machine
Learning Repository 

MLC++  a library of C++
classes for supervised machine learning. 

BNJ  Bayesian Network tools
in Java


UnBBayes  a probabilistic
network framework written in Java. 

MLJ  Machine Learning in
Java 
