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K-Means Clustering
Number of Clusters (K):
3
Data Points:
200
Animation Speed:
1
Generate New Data
Step
Run/Pause
Iteration:
0
Converged:
No
Total Inertia:
-
K-Means Algorithm
1. Initialize K random centroids
2. Assign each point to nearest centroid
3. Update centroids to cluster means
4. Repeat until convergence
Watch how centroids move and clusters stabilize!