An analysis of the application of simplified silhouette to the evaluation of k-means clustering validity

Abstract

This paper analyses the application of Simplified Silhouette to the evaluation of k-means clustering validity and compares it with the k-means Cost Function and the original Silhouette. We conclude that for a given dataset the k-means Cost Function is the most valid and efficient measure in the evaluation of the validity of k-means clustering with the same k value, but that Simplified Silhouette is more suitable than the original Silhouette in the selection of the best result from kmeans clustering with different k values.