Semantic Variable Clustering

Context

• Semantic Variable Clustering groups nodes based on the semantics of their Node Names.

Usage & Example

• For this example, we use a list of 49 positive character traits.

• All character traits are represented by nodes in an unconnected Bayesian network.

• The nodes are named after character traits; no other information is available, e.g., in the Node Long Names or the Node Comments.

• Select all nodes you wish to cluster.

• To start the Semantic Variable Clustering, select Main Menu > Hellixia > Semantic Variable Clustering.

• In the Semantic Variable Clustering window, you can specify the following item:

  • Your Completion Model, which depends on your OpenAI subscription

  • The Context that may apply to the nodes to be clustered

  • The Maximum Number of Clusters allows you to limit how many clusters are generated.

• Clicking OK initiates Hellixia's communication with ChatGPT.

• Upon completing the task, BayesiaLab presents the Semantic Variable Clustering Report in a new window.

Semantic Variable Clustering Report

• These newly-created clusters are now represented as Classes, indicated by the Classes icon .

Workflow Illustrations