Configuration
Number of clusters K
3
Show Voronoi regions
K-Means++ init
Show centroids trail
Actions
Status
Points0
Iteration0
WCSSβ
Convergedβ
Elbow Method
Legend
K-Means: Assign each point to nearest centroid, then
move centroids to cluster mean. Repeat until convergence.
K-Means++: Smarter initialisation β each centroid chosen with probability β dΒ² from nearest existing centroid.
Elbow Method: Plot WCSS vs K; optimal K is at the "elbow" bend.
K-Means++: Smarter initialisation β each centroid chosen with probability β dΒ² from nearest existing centroid.
Elbow Method: Plot WCSS vs K; optimal K is at the "elbow" bend.