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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
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Naive Bayes |
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TAN - tree augmented naive Bayes |
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FAN - forest augmented naive Bayes
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STAN - selective tree augmented
naive Bayes |
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STAND - selective tree augmented
naive Bayes with node discarding |
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SFAN - selective forest augmented
naive Bayes |
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STAND - selective forest augmented
naive Bayes with node discarding |
Network Quality Measures
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HGC - Heckerman-Geiger-Chickering |
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SB - Standard Bayesian |
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LC - Local criterion |
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LOO - Leave-One-Out cross
validation |
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CVn,t - n
-fold t-times 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.
jBNC-WEKA
jBNC-WEKA 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
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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. |
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N. Friedman, D. Geiger, and M. Goldszmidt.
"Bayesian network classifiers", Machine
Learning, 29:2/3, 1997.
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Related Links
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applet.JavaBayes
-
Bayesian Networks in Java
|
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GNU getopt - Java port
|
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Weka - a collection of
machine learning algorithms in Java |
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KDD -
data mining, knowledge discovery, genomic mining, and web mining
resources
|
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UCI Machine
Learning Repository |
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MLC++ - a library of C++
classes for supervised machine learning. |
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BNJ - Bayesian Network tools
in Java
|
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UnBBayes - a probabilistic
network framework written in Java. |
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MLJ - Machine Learning in
Java |
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