K-Means Clustering Details

The Model Detail screen includes the following information for K-Means Clustering models:

Model Summary
  • Number of Rows
  • Number of Clusters
  • Number of Categorical Columns
  • Number of Iterations
  • Within Cluster Sum of Squares
  • Total Sum of Squares
  • Between Cluster Sum of Squares

Metrics

Provides training, test, and n-fold data for the following:
  • Total within cluster sum of squares
  • Total sum of squares
  • Between cluster sum of squares

Centroid Statistics

Provides the following training, test, and n-fold data for each centroid:
  • Size
  • Within cluster sum of squares

Cluster Means

Provides detailed information for each centroid. Content varies based on input data. A cluster is a group of observations from a data set identified as similar according to a particular clustering algorithm

Standardized Cluster Means

Provides standardized information for each centroid. Content varies based on input data.