Cluster modeling example

The Model Summary page provides basic information about the auto cluster model algorithm that was used (TwoStep, in this example), the number of auto clusters found, and a basic idea of cluster quality.

Other charts are also available. You can hover over various areas in each chart to see more detail, and interact with some of the charts (such as the Predictor Importance chart).

Using the Clusters view (the last chart), you can also compare clusters to look for interesting patterns. In a real world implementation, you would study the auto clusters and then give them more meaningful names (by clicking each cluster label in the Clusters view). After updating the cluster label names, the new names will be used in all other charts and back on the Modeling tab. Then you would proceed to evaluate and test the model, and finally score it once you're happy with it.