K-Means Clustering Details
The Model Detail screen includes the following information for K-Means Clustering models:
Model Summary
Provides training data for the following:
- 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.