Software for Learning Belief
Networks from Data
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[Manipulation | Learning from Data | Glossary |
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Software for Learning Belief
Networks from Data
This document describes software for fitting
graphical belief function models, and
related modes such as
Bayesian networks,
influence diagrams, and
probabilistic graphical models from
data, or learning with existing model structures.
This page only describes software which fits models to data.
For manipulating already constructed models, see the manipulating belief models page.
Each entry on this list contains information about features of the
software and contact information. Pricing information includes the
date the price was last updated as this information may vary from time
to time (based on past performance, I'm rather slow about updating
this list). Hyperlinks take you demo versions (or actual software for free
software) when it is available on-line.
A key to terms used in the feature lists
and a list of references are available below.
Packages reviewed in this document:
"+" indicates new since last version
"*" indicates changed since last version
This is version 1.4.
Scope, Purpose and Remarks
Building this list of software is more difficult than the
corresponding one for fitting models because
of the difficulty of defining the scope of this project. Clearly both
general purpose statistical or knowledge discovery tools could fall
under the umpbrella of this project. In particular, many log-linear
models, path analysis and regression models are graphical models, so
any statistics package capable of performing regression could
potentially be included (Whittaker[1990] provides a good
description of the link between statistics and graphical models).
This is obviously far more work than I'm willing to entertain.
Similarly, I've decided that packages which support tree-based models
(e.g., CART) or neural networks are outside the scope of this
page (although there may be enough conceptual similarity to justify
their inclusion).
The packages described here specifically support graphical models
with nodes representing variables and edges interactions in either
their inputs or their outputs. People interested in other kinds of
software are encouraged to check out these sources:
Also, a number of the packages for manipulating graphical belief
models support updating of parameters from data. These include
HUGIN and
XBaies.
Software in this first list is free for educational and research
purposes. In some cases it may be more freely used. Each listing
includes any restrictions on the use of the software.
Hypertext links to the actual software or product
descriptions are provided where available.
- Description:
- BIFROST fits block recursive models (chain graphs) to data. It
works with the program CoCo to do the
fitting and will export models in a form that can be read by Hugin for analysis.
- Scope:
- Discrete Graphical Models, Chain Graphs
- Features:
- Model Selection, Export to Hugin
- Platforms:
- Runs on top of CoCo.
- Documentation:
- R92-2001,
R92-2010
- Program:
- Bifrost1.1
- Contact:
- Bo Thiesson (thiesson@iesd.auc.dk)
[Return to Table Of Contents]
- Description:
- BNG isn't really software for learning belief networks, rather
it is software for building belief networks
- Scope:
- Discrete Graphical Models
- Features:
- Knowledge Based Model Construction
- Platforms:
- Common Lisp, generates rule bases for IDEAL.
- Program:
- Software Descriptions
- References:
- Ngo, Haddawy and Helwig [1995],
Haddawy et al[1995],
Haddawy [1994].
- Contact:
- Peter Haddawy
(haddawy@sprecher.cs.uwm.edu )
[Return to Table Of Contents]
- Description:
- BUGS is a general purpose Markov Chain Monte Carlo program
(Gibbs sampler) which because of its input syntax is
particularly easy to use with graphical models.
- Scope:
- Graphical Models, Mixed Models, Latent Variables, Missing Data,
General Bayesian Inference.
- Features:
- Comes with CODA a suit of S-Plus tools for assessing convergence.
- Platforms:
- Unix and Dos.
- Restrictions:
- Registration Required
- Home Page:
- England
US Mirror
- Documentation:
- Documentation and Worked Examples.
- Program:
- Software Download and Registration
- Contact:
- bugs@mrc-bsu.cam.ac.ukat the MRC Biostatistics Unit
- Notes:
- If you have trouble accessing the files from here, try using
ftp at ftp.mrc-bsu.cam.ac.uk and look in the directory
/pub/metholodogy/bugs, or try the US Mirror
- Warning:
- Gibbs Sampling can be Dangerous! It allows you to fit
any model you like to any data, no matter how stupid. Make
sure you know what you're doing.
[Return to Table Of Contents]
- Description:
- CoCo fits contingency tables to graphical models through a
variety of selection procedures.
- Scope:
- Discrete Graphical Models
- Features:
- Model Selection, Graphical Interface in XLISP-STAT and link to S-Plus.
- Platforms:
- Macintosh (old version), Windows and Unix (latest)
- Documentation:
- See the CoCo
Information Page
- Program:
- CoCo can be obtained from
iesd.auc.dk in Denmark, or from the USA Mirror
stat.ucla.edu.
- Contact:
- Jens Henrik
Badsberg
(jhb@iesd.auc.dk)
[Return to Table Of Contents]
- Description:
- MIM is a general purpose package for fitting graphical and hierarchical models
to mixed discrete and continuous data using maximum likelihood estimation.
- Scope:
- Graphical Models, Hierarchical Interaction Models.
- Features:
- GUI, Statistical Tests, Model Selection, Latent Variables, Diagnostic Graphics
- Platforms:
- DOS, Windows
- Price:
- Single-user License US $250, Multi-user License $1000, Student Version
free. (Dec, 1995).
- Demo:
- student version
(of MIM 2.3 for Windows)
Statlib Mirror
- Contact:
- David Edwards (DEd@novo.dk)
- More information:
-
MIM Information Page
- Reference:
- Edwards [1995] (This book is
the complete reference for MIM and contains a copy of the student version for DOS).
[Return to Table Of Contents]
- Description:
- A multi-module program that assists in the construction of
causal explanations for sample daata and their use in
prediction.
- Scope:
- Discrete Bayesian Networks, Path Models and Structural Equation
Models (directly estimates discrete networks, but creates input
code to LISREL, EQS or CALIS, which are available elsewhere,
for other models).
- Features:
- Model Search, Latent Variables, Simulation, Bayesian Updating
- Platforms:
- DOS
- Price:
- $150, DOS program with examples and user's maual
- Contact:
-
Richard Scheines
(Scheines@andrew.cmu.edu)
Or order from
Lawrence Erlbaum Associates
10 Industrial Ave
Mahwah, NJ 07430-22262
1-800-926-6579
1-201-236-9500
1-201-236-0072 (fax)
- More Information:
- The TETRAD
Project Homepage
- Reference:
- Scheines \ea [1994] (This book is
the reference for TETRAD and contains a copy of the software).
[Return to Table Of Contents]
[Manipulation | Learning from Data | Glossary |
References ]
This list is maintained by Russell G. Almond.
Software for Fitting Belief Networks / almond@acm.org
Please send me any updates, corrections, omissions or suggestions for
improvement. This is version 1.4 (3/2/95), so please bear with any
mistakes. (As this is just a minor bug fix since the last release,
I've left the "new" and "changed" markers from the 1.0 to 1.3
updagrade.) The next version should include information of model
fitting software. Please send contributions to me.
Thanks to David
Madigan and the University of Washington
Statistics Department for hosting this Web page.
Last modified: Thu May 30 14:27:50 1996