Cluster Interpretation: Relationship with Target Node

Background & Context

• On this page, we present the Relationship with Target Node report for cluster interpretation as an alternative to Most Relevant Explanations for Cluster Interpretation.

• To provide further context for Most Relevant Explanations for Cluster Interpretation, we compare several other approaches that can help interpret individual Clusters:

  • Setting Evidence for Cluster Interpretation: Posterior Distributions, Relationship with Target Node, Mosaic Analysis, Posterior Mean Analysis, Segment Profile Analysis, Histograms, Tornado Diagrams,
  • Optimization for Cluster Interpretation: Dynamic Profile, Target Optimization Tree

• More specifically, we compare all these approaches with regard to characterizing the state $\mathit{Cluster\ 3}$ of the Cluster Node $\mathit{Factor}_0$ in the reference network.

• All analyses and instructions on this page refer to this reference network, which you can download here:

  MaleClusters.xbl

Relationship with Target Node

• To produce the Relationship with Target Node report, select Main Menu > Analysis > Report > Target > Relationship with Target Node.

  

• In addition to a wide range of information about the Target Node in general and other states, we obtain a list of measures specific to Cluster $\mathit{C3}$:

  • Node: name of the node to which all measures of the row apply.
  • Binary Mutual Information: the amount of information gained by observing the node regarding the Target State ($\mathit{C3}$) of the Target Node $\mathit{Factor}_0$.
    • Note that in an earlier table within this report, BayesiaLab reports the Mutual Information of the node regarding the Target Node in general.
  • Relative Binary Mutual Information: the amount of information gained by observing the node regarding the Target State ($\mathit{C3}$) of the Target Node $\mathit{Factor}_0$, divided by the marginal Entropy of the Target State.
  • Binary Relative Significance: the proportion of the node’s Binary Mutual Information relative to the node with the maximum Binary Mutual Information. As a result, the top row always features a Binary Relative Significance of 1.
  • Posterior Mean Value: the expected value of the node given Target State ($\mathit{C3}$) of the Target Node $\mathit{Factor}_0$.
  • The Max Bayes Factor heading spans three unlabeled columns:
    • Node State that corresponds to the maximum Bayes Factor for that node regarding Target State ($\mathit{C3}$) of the Target Node $\mathit{Factor}_0$, including the State Value (or State Name).
    • Probability of the Node State with the maximum Bayes Factor.
    • Bayes Factor calculated for that state.
  • The Min Bayes Factor heading spans three unlabeled columns:
    • Node State that corresponds to the minimum Bayes Factor for that node regarding Target State ($\mathit{C3}$) of the Target Node $\mathit{Factor}_0$, including the State Value (or State Name).
    • Probability of the Node State with the minimum Bayes Factor.
    • Bayes Factor of the Node State with the minimum Bayes Factor.