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Designing Graphical Causal Bayesian Networks in Python

Synthetic Nodes

Explore how synthetic nodes can reduce the exponential growth of Conditional Probability Distributions in Bayesian networks by simplifying complex parent-child relationships. This lesson helps you understand the curse of dimensionality and implement synthetic nodes in Python to enhance model speed, accuracy, and clarity in causal structures.

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The size of a CPD table

In a Bayesian network, the size of the CPD table for a child node depends on the number of parent nodes.

For NN parent nodes, each having kk possible values, there will be kNk^{N}different combinations. The child node itself can also have mm possible values. Therefore, mm represents the number of possible values (or states) for the child node. Just as kk ...