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