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 - Heckerman-Geiger-Chickering
	SB - Standard Bayesian
	LC - Local criterion
	LOO - Leave-One-Out cross validation
	CVn,t - n -fold t-times Cross Validation

jBNC-WEKA

References

	J.P. Sacha, L. Goodenday, and K.J. Cios. "Bayesian learning for cardiac SPECT image interpretation", Artificial Intelligence in Medicine, 26, pp.109-143, 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