A note on cluster validity indices SV and OS

Krista Rizman Zalik and Borut Zalik proposed indices SV and OS associating with separation and compactness or overlap. Compactness and overlap were calculated by a few data points of a cluster, which makes the indices able to identify the number of clusters underlying the data set of different sizes and densities. However, the measure of overlap depends on two undefined variants and the measure of compactness are build on randomly selected ten percent data points of a cluster, which makes them difficult to compute and unpractical. This paper supposes to measure the compactness using ten percent of data points of a cluster that are farthest away from the center of the cluster, and revises the measure of overlap so that two undefined variants are eliminated from the measure of overlap. Experiments show that the modified index SV can identify the optional number of clusters underlying the data set of different size and prefers to the index Os.