Cluster Analysis Calculator
Group data points into clusters using K-means or hierarchical methods.
Clustering Results (K-Means)
Points:6
Clusters:3
Iterations:2
WCSS:14.8117
Cluster Assignments
| Point | Coordinates | Cluster | Silhouette |
|---|---|---|---|
| 1 | [1.00, 2.00] | 3 | 0.615 |
| 2 | [1.50, 1.80] | 3 | 0.586 |
| 3 | [5.00, 8.00] | 1 | 0.581 |
| 4 | [6.00, 8.00] | 1 | 0.661 |
| 5 | [1.00, 0.60] | 2 | 1.000 |
| 6 | [9.00, 11.00] | 1 | 0.613 |
Cluster Centroids
Cluster 1[6.667, 9.000](3 points)
Cluster 2[1.000, 0.600](1 points)
Cluster 3[1.250, 1.900](2 points)
Quality Metrics
Average Silhouette Score: 0.676 (Good clustering)