Bisecting K-Means Clustering
Divisive hierarchical clustering with K-Means bisection
Clusters
—
via bisecting
Inertia
—
Sum of squared distances
Silhouette
—
Weak separation
Strategy
—
Split highest variance
Initialization
—
1 run per split
Duration
—
Bisection + full metrics
Cluster Visualization
Interactive scatter plot with cluster centroids
Run training to render the scatter plot
Deep Dive Analysis
Advanced metrics and interpretation tools
Silhouette Analysis
Per-sample quality scores grouped by cluster
Mean
0.000
Best
0.000
Worst
0.000
Enable per-sample metrics during training to generate cluster-level silhouette coefficients.
Job History
Recent jobs — auto-pruned to keep 10 per type
No jobs recorded yet. Run a clustering, classification, or pipeline job to see results here.