Cluster Analysis Calculator
Group data points into clusters using K-means or hierarchical methods.
Clustering Results (K-Means)
Points:6
Clusters:3
Iterations:1
WCSS:1.8133
Cluster Assignments
| Point | Coordinates | Cluster | Silhouette |
|---|---|---|---|
| 1 | [1.00, 2.00] | 3 | 0.871 |
| 2 | [1.50, 1.80] | 3 | 0.876 |
| 3 | [5.00, 8.00] | 2 | 0.800 |
| 4 | [6.00, 8.00] | 2 | 0.764 |
| 5 | [1.00, 0.60] | 3 | 0.844 |
| 6 | [9.00, 11.00] | 1 | 1.000 |
Cluster Centroids
Cluster 1[9.000, 11.000](1 points)
Cluster 2[5.500, 8.000](2 points)
Cluster 3[1.167, 1.467](3 points)
Quality Metrics
Average Silhouette Score: 0.859 (Good clustering)