Parameter Estimation with Trees (9.0)

Overview & Context

In BayesiaLab, a Conditional Probability Distribution (CPD) can be compactly represented with a Conditional Probability Tree (CPTr), which takes advantage of Contextual Independencies. A Contextual Independence exists if a particular state of a parent node makes the other co-parent(s), i.e., the spouse(s), independent of the child node.

New Feature: EQ, TabooEQ, and SopLEQ

As of version 9.0, all unsupervised structural learning algorithms are compatible with estimating probabilities with Conditional Probability Trees.

Usage

To use Conditional Probability Trees for estimation, select Edit > Parameter Estimation with Trees from the Main Menu. Alternatively, you can select Parameter Estimation with Trees from the Graph Contextual Menu.