From 8070dc963753142bb86c4ed698d91fd623ed28e7 Mon Sep 17 00:00:00 2001 From: ziejd2 Date: Thu, 28 Sep 2017 15:04:40 -0500 Subject: BNW using Octave instead of Matlab. This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning. I am calling this BNW_1.02. It can be accessed at: compbio.uthsc.edu/BNW_1.02 --- sourcecodes/bnt-master/docs/bnsoftOld.html | 1078 ++++++++++++++++++++++++++++ 1 file changed, 1078 insertions(+) create mode 100644 sourcecodes/bnt-master/docs/bnsoftOld.html (limited to 'sourcecodes/bnt-master/docs/bnsoftOld.html') diff --git a/sourcecodes/bnt-master/docs/bnsoftOld.html b/sourcecodes/bnt-master/docs/bnsoftOld.html new file mode 100644 index 00000000..9da92fa1 --- /dev/null +++ b/sourcecodes/bnt-master/docs/bnsoftOld.html @@ -0,0 +1,1078 @@ + +Software Packages for Graphical Models / Bayesian Networks + + + + +

+Software Packages for Graphical Models / Bayesian Networks +

+

+Written by Kevin Murphy. +
+Last updated 31 October 2005. + +

Remarks

+ + +

What do the headers in the table mean?

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Name + Authors + Src + API + Exec + Cts + GUI + Params + Struct + Utility + Free + Undir + Inference + Comments + + +
AgenaRisk + Agena + N + Y + W,U + Cx + Y + Y + N + N + $ + D + JTree + Simulation by Dynamic discretisation + +
Analytica + Lumina + N + Y + W,M + G + Y + N + N + Y + $ + D + sampling + spread sheet compatible + +
Banjo + Hartemink + Java + Y + W,U,M + Cd + N + N + Y + N + 0 + D + none + structure learning of +static or dynamic networks of discrete variables + + +
Bassist + U. Helsinki + C++ + Y + U + G + N + Y + N + N + 0 + D + MH + Generates C++ for MCMC. + +
Bayda + U. Helsinki + Java + Y + WUM + G + Y + Y + N + N + 0 + D + ? + Bayesian Naive Bayes classifier. + +
BayesBuilder + Nijman (U. Nijmegen) + N + N + W + D + Y + N + N + N + 0 + D + ? + - + +
BayesiaLab + Bayesia Ltd + N + N + - + Cd + Y + Y + Y + N + $ + CG + jtree,G + + +Structural learning, adaptive +questionnaires, dynamic models + + + + +
Bayesware Discoverer + Bayesware + N + N + WUM + Cd + Y + Y + Y + N + $ + D + ? + Uses bound and collapse for learning with missing data. + +
B-course + U. Helsinki + N + N + WUM + Cd + Y + Y + Y + N + 0 + D + ? + Runs on their server: view results using a web browser. + + + +
Belief net power constructor + Cheng (U.Alberta) + N + W + W + D + Y + Y + CI + N + 0 + D + ? + - + +
BNT + Murphy (U.C.Berkeley) + Matlab/C + Y + WUM + G + N + Y + Y + Y + 0 + D,U + Many + Also handles dynamic models, like HMMs and Kalman filters. + + +
BNJ + Hsu (Kansas) + Java + - + - + D + Y + N + Y + N + 0 + D + jtree, IS + - + + + +
BucketElim + Rish (U.C.Irvine) + C++ + Y + WU + D + N + N + N + N + 0 + D + Varelim + - + +
BUGS + MRC/Imperial College + N + N + WU + Cs + W + Y + N + N + 0 + D + Gibbs + - + +
Business Navigator 5 + Data Digest Corp + N + N + W + Cd + Y + Y + Y + N + $ + D + Jtree + - + +
CABeN + Cousins et al. (Wash. U.) + C + Y + WU + D + N + N + N + N + 0 + D + 5 Sampling methods + - + +
Causal discoverer + Vanderbilt + N + N + W + - + - + N + Y + N + 0 + D + - + structure learning only + + +
CoCo+Xlisp + Badsberg (U. Aalborg) + C/lisp + Y + U + D + Y + Y + CI + N + 0 + U + Jtree + Designed for contingency tables. + +
CIspace + Poole et al. (UBC) + Java + N + WU + D + Y + N + N + N + 0 + D + Varelim + - + +
DBNbox + Roberts et al + Matlab + - + - + Y + N + Y + N + N + + Y + D + Various + DBNs + +
Deal + Bottcher et al + R + - + - + G + Y + Y + Y + N + 0 + D + None + +Structure learning. + +
DeriveIt + DeriveIt LLC + N + - + - + ? + ? + Y + Y + ? + $ + D + Jtree + +Exploits local structure in CPDs. + + +
Ergo + Noetic systems + N + Y + W,M + D + Y + N + N + N + $ + D + jtree + - + + + +
GDAGsim + Wilkinson (U. Newcastle) + C + Y + WUM + G + N + N + N + N + 0 + D + Exact + Bayesian analysis of large linear Gaussian directed models. + + +
Genie + U. Pittsburgh + N + WU + WU + D + W + N + N + Y + 0 + D + Jtree + - + +
GMRFsim + Rue (U. Trondheim) + C + Y + WUM + G + N + N + N + N + 0 + U + MCMC + Bayesian analysis of large linear Gaussian undirected models. + + +
GMTk + Bilmes (UW), Zweig (IBM) + N + Y + U + D + N + Y + Y + N + 0 + D + Jtree + +Designed for speech recognition. + +
gR + Lauritzen et al. + R + - + - + - + - + - + - + - + 0 + - + - + Currently vaporware + + +
Grappa + Green (Bristol) + R + - + - + D + N + N) + N + N + 0 + D + Jtree + - + + +
Hugin Expert + Hugin + N + Y + W + G + W + Y + CI + Y + $ + CG + Jtree + - + + +
Hydra + Warnes (U.Wash.) + Java + - + - + Cs + Y + Y + N + N + 0 + U,D + MCMC + - + + +
Ideal + Rockwell + Lisp + Y + WUM + D + Y + N + N + Y + 0 + D + Jtree + GUI requires Allegro Lisp. + +
Java Bayes + Cozman (CMU) + Java + Y + WUM + D + Y + N + N + Y + 0 + D + Varelim, jtree + - + + +
KBaseAI + Codeas + N + Y + W,U + D + N + N + N + N + $ + D + varelim + client/server architecture, multiple users, access +control, query language + + +
LibB + Friedman (Hebrew U) + N + Y + W + D + N + Y + Y + N + 0 + D + none + +Structure learning + +
MIM + HyperGraph Software + N + N + W + G + Y + Y + Y + N + $ + CG + Jtree + Up to 52 variables. + +
MSBNx + Microsoft + N + Y + W + D + W + N + N + Y + 0 + D + Jtree + - + +
Netica + Norsys + N + WUM + W + G + W + Y + N + Y + $ + D + jtree + - + +
Optimal +Reinsertion + Moore, Wong (CMU) + N + N + W,U + D + N + Y + Y + N + 0 + D + none + structure learning + + +
PMT + Pavlovic (BU) + Matlab/C + - + - + D + N + Y + N + N + 0 + D + special purpose + - + + + +
PNL + Eruhimov (Intel) + C++ + - + - + D + N + Y + Y + N + 0 + U,D + Jtree + +A C++ version of BNT; will be released 12/03. + + +
Pulcinella + IRIDIA + Lisp + Y + WUM + D + Y + N + N + N + 0 + D + ? + Uses valuation systems for non-probabilistic calculi. + +
RISO + Dodier (U.Colorado) + Java + Y + WUM + G + Y + N + N + N + 0 + D + Polytree + Distributed implementation. + + + +
Sam Iam + Darwiche (UCLA) + N + N ? + WU ? (Java executable) + G ? + Y + Y + N ? + Y + 0 + D + Recursive conditioning + Also does sensitivity Analysis + + +
Tetrad + CMU + N + N + WU + G + N + Y + CI + N + 0 + U,D + None + - + + +
UnBBayes + ? + Java + - + - + D + Y + N + Y + N + 0 + D + jtree + K2 for struct learning + + +
Vibes + Winn & Bishop (U. Cambridge) + Java + Y + WU + Cx + Y + Y + N + N + 0 + D + Variational + +Not yet available. + + +
Web Weaver + Xiang (U.Regina) + Java + Y + WUM + D + Y + N + N + Y + 0 + D + ? + - + +
WinMine + Microsoft + N + N + W + Cx + Y + Y + Y + N + 0 + U,D + None + Learns BN or dependency net structure. + +
XBAIES 2.0 + Cowell (City U.) + N + N + W + G + Y + Y + N + Y + 0 + CG + Jtree + - + +
+ + +

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Other sites related to (software for) graphical models

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