6/16/2010 - The MSBNx sample code is now available for C# 4 and VS2010: SamplesCSharp2010.zip
9/20/2007 - The MSBNx sample code is now available in C#: SamplesCSharp.zip
1/31/2007 -- The first time you run MSBNx under Windows Vista, you'll get this pop-up message: "DLL Self-registration failed for HMMAddinLib.dll". Click "OK" and ignore the message.
08/02/2001 -- Before installing a new version, you must uninstall the previous version.
08/02/2001 - Reading models from the WinMine tool not supported for now. We are working on the issue.
08/01/2001 - Released version 220.127.116.11 - changes the default Value of Information measure for diagnosis to entropic. This avoids a problem with the KL-distance based measure.
MSBNx is a component-based Windows application for creating, assessing, and evaluating Bayesian Networks, created at Microsoft Research. The application's installation module includes complete help files and sample networks. Bayesian Networks are encoded in an XML file format. The application and its components run on Windows 98, Windows 2000, and Windows XP.
Comments and Questions
Please email firstname.lastname@example.org with your comments or questions.
See the Background page for information on how Bayesian Networks are useful for diagnose and troubleshooting.
When doing diagnosis and troubleshooting, MSBNx can recommend what evidence to gather next.
If you give MSBNx cost information, it does a cost-benefit analysis. If no cost information is available, MSBNx makes recommendations based on the Value of Information (VOI).
MSBNx tries to make it easy for you to specify your probabilities for a Bayesian Network.
Use It in Programs
MSBNx is fully component based. Its most important component is MSBN3, an ActiveX DLL. MSBN3 offers an extensive COM-based API for editing and evaluating Bayesian Networks. You'll find MSBN3 especially easy to use from COM-friendly languages such as Visual Basic and JScript.
MSBNx also includes graphical components, for example, both the Standard Assessment and Asymmetric Assessment tools are ActiveX controls and can be used in other applications.
Also, you can extend the editing and evaluation abilities of MSBNx by creating add-ins. For example, MSBNx ships with an add-in for editing and evaluating Hidden Markov Models.
More Information about MSBNx
You can read about MSBNx in this tech report:
C.M. Kadie, D. Hovel, and
E. Horvitz. MSBNx: A
Component-Centric Toolkit for
You may also wish to peruse the comprehensive manuals for MSBNx
An extensive manual documents MSBNx.
A comprehensive manual documents MSBN3.
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See the end-user license agreement (EULA) for limitations of liability and support.