k-Means Algorithm
Step 1: Analyst specifies k = number of clusters to partition data
Step 2: k records randomly assigned to initial clusters
Step 3: For each record, find cluster center
Each cluster center “owns” subset of records
Results in k clusters, C1, C2, ...., Ck
Step 4: For each of k clusters, find cluster centroid
Update cluster center location to centroid
Step 5: Repeats Steps 3 – 5 until convergence or termination