| (1) Input: Data SET , Attribute Set ), Cluster Number (), |
| (2) Output: Clusters Seed-Set |
| (3) Begin |
| (4) While () |
| (4.1) Compute Standard Deviation () and Mean () |
| (4.2) Compute Cluster Center |
| |
| (4.3) Execute -means on this attribute |
| (4.4) Allocate cluster labels obtained from Step (4.3) to every data pattern |
| (5) Find unique patterns () and clustering each data with obtained patterns. |
| (6) Return SC |
| (7) End |