Quality of Clusterings Two metrics: –SSE –Dissimilarity Ratio

Computing SSE Save clusters. Two new columns are created: Cluster and Distance. Create new column as formula. Name it as dist-sqr and define it as Distance 2 Analyze – Distribution for dist-sqr. Get the mean and multiply by N to obtain SSE

Computing Dissimilarity Ratio Dissimilarity ratio = (inter-cluster distance / intra- cluster distance) Inter-cluster distance is the smallest distance between centroids Normalize centroid coordinates: –Coordinates are given in cluster output –Find mean and std dev for each dimension from histogram (distribution) output –Normalize each centroid coordinate: (x - mean) /st dev –Compute distances between each pair of centroids: Inter-cluster distance is given by the smallest of the normalized centroid distances

Dissimilarity Ratio – cont. Intra-cluster distance is given by the average max dist of the clusters. The max dist of each cluster is found at the clusters output in JMP. Computer dissimilarity ratio (DR) for each clustering The higher the DR the better the clustering.