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BayesiaLabPrevious ReleasesBayesiaLab 5.0.2Analysis (5.0.2)Report (5.0.2)Information Analysis (5.0.2)

Information Analysis (5.0.2)

Overview

Information analysis with three sets of nodes (X, Y, and Z)

Clicking on the Select Nodes buttons allows defining three sets of nodes for analysis. The selection is done by directly selecting the nodes in the graph. By default, the Target node is associated with the Y set.

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Information Analysis Report

Given the exponential growth of the state space, this analysis is only performed on the database.

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Unconditional Entropy

H(X)=−∑x∈Xp(x)log⁡2(p(x))H(X) = -\sum_{x \in X} p(x) \log_2(p(x))
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Conditional Entropy

H(X∣Z)=−∑z∈Zp(z)∑x∈Xp(x∣z)log⁡2(p(x∣z))H(X|Z) = -\sum_{z \in Z} p(z) \sum_{x \in X} p(x|z) \log_2(p(x|z))
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Unconditional Mutual Information

I(X,Y)=H(X)−H(X∣Y)I(X, Y) = H(X) - H(X|Y)
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Conditional Mutual Information

I(X,Y∣Z)=H(X∣Z)−H(X∣Y,Z)I(X, Y|Z) = H(X|Z) - H(X|Y,Z)
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Total Correlation

C(X)=∑iH(xi)−H(X)C(X) = \sum_i H(x_i) - H(X)
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Conditional Total Correlation

C(X∣Z)=∑iH(xi∣Z)−H(X∣Z)C(X|Z) = \sum_i H(x_i|Z) - H(X|Z)
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Evidence Analysis with respect to the Target Node (5.0.2)Target Analysis (5.0.2)
Information Analysis (5.0.2) – Bayesia