Overview

Follow the links below to access resources with abudant information Bayesian Networks.

Brief Intro

A brief introduction to Graphical Models and Bayesian Networks by Kevin Murphy (since 1998).

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Bayesian Nets Tutorial

A paper that discusses methods for constructing Bayesian networks from prior knowledge and summarize Bayesian statistical methods for using data to improve these models.

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Microsoft BN Editor

Microsoft Bayesian Network Editor - a component-based Windows application for creating, assessing, and evaluating Bayesian Networks, created at Microsoft Research.

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More Info on the Web

A great resource of information is the Wikipedia Bayesian network page.

Software Implementations

There are numerous software implementations for the Bayesian networks. The most popular implementations are listed below.

Java SDK Required

There are two types of downloads for the Weka Machine learning package: one that includes the JVM, and the other that assumes you have it already installed. If you don't have Java on your machine download the bigger package.

The Weka Data Mining Software

This package makes available most Machine Learning algorithms as tools for data pre-processing, classification, regression, clustering, association rules, and visualization, wich can be applied to practical problems.

The Weka machine learning package can be downloaded from the Waikato University machine learning site.

The Tetrad Project

Tetrad is a program which creates, simulates data from, estimates, tests, predicts with, and searches for causal and statistical models. The aim of the program is to provide sophisticated methods in a friendly interface requiring very little statistical sophistication of the user and no programming knowledge.

The Tetrad packages can be downloaded from Tetrad page.

About

This web site was built to help all those who want to learn and get a deep understanding about Bayesian Networks.

Contact

For questions or suggestions on how to improve this site please email Marin Kokona with user name mar1n at Yahoo! email.