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