A Modification of the Silhouette Index for the Improvement of Cluster Validity Assessment

In this paper a modification of the well-known Silhouette validity index is proposed. This index, which can be considered a measure of the data set partitioning accuracy, enjoys significant popularity and is often used by researchers. The proposed modification involves using an additional component in the original index. This approach improves performance of the index and provides better results during a clustering process, especially when changes of cluster separability are big. The new version of the index is called the SILA index and its maximum value identifies the best clustering scheme. The performance of the new index is demonstrated for several data sets, where the popular algorithm has been applied as underlying clustering techniques, namely the Complete–linkage algorithm. The results prove superiority of the new approach as compared to the original Silhouette validity index.

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