- BayesiaLab
Bayesian network laboratory producing a broad set of tools for structure learning, analysis, adaptive questionnaires, and dynamic Bayesian networks
http://www.bayesia.com
(Added: Thu Jan 01 2004 Hits: 0 Rating: 0.00 Votes: 0)
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Review It - CleverSet, Inc.
Develops and exploits proprietary Relational Bayesian Modeling (RBM) technology and applications that provide real-time, actionable results from large amounts of dynamic, multi-faceted, ambiguous information.
http://www.cleverset.com
(Added: Thu Jan 01 2004 Hits: 0 Rating: 0.00 Votes: 0)
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Review It - DEAL
Open source package for the technical computing language R, developed by Aalborg University and Novo Nordisk A/S - analysis and structure learning of Bayesian networks with discrete and/or continuous variables
http://www.math.auc.dk/novo/deal
(Added: Thu Jan 01 2004 Hits: 0 Rating: 0.00 Votes: 0)
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Review It - Genie/Smile
GeNIe is a development environment for building graphical decision-theoretic models running under Windows operating systems. SMILE is its portable inference engine, consisting of a library of C++ classes, currently compiled for Windows, Solaris and Linux.
http://www2.sis.pitt.edu/~genie/
(Added: Thu Jan 01 2004 Hits: 0 Rating: 0.00 Votes: 0)
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Review It - Knowledge Industries, Inc.
Builds and licenses diagnostic software based upon Bayesian Belief Networks for medical, industrial and management applications. Software includes editors/compilers, test/review tools and inference engines embeddable in stand-alone and web-based applications.
http://www.kic.com
(Added: Thu Jan 01 2004 Hits: 0 Rating: 0.00 Votes: 0)
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Review It - RISO
Robert Dodier's open source package for distributed, heterogeneous belief networks in Java - allows different conditional distributions
http://riso.sourceforge.net
(Added: Thu Jan 01 2004 Hits: 0 Rating: 0.00 Votes: 0)
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Review It - WebWEavr-III
WEBWEAVR-III is a Java application that supports the construction of Bayesian networks, inference in standard and dynamic Bayesian networks and decomposable Markov networks, construction and verification of multiply-sectioned Bayesian networks (MSBNs), inference in multi-agent MSBNs, and learning decomposable Markov networks.
http://snowhite.cis.uoguelph.ca/faculty_info/yxiang/ww3/
(Added: Thu Jan 01 2004 Hits: 0 Rating: 0.00 Votes: 0)
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