Semantic Variable Clustering


  • 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