Journals Proceedings

Abstract

In this study, commonly used proximity measures, in other words, distance and similarity functions are reviewed. An interactive software tool with graphical user interface is developed to examine the effect of proximity measures on the performance of clustering methods. The software named ClustProX allows the users to select a data set, to apply a clustering method and to observe the performance of the results. Xie-Beni and Kwon indices are used to evaluate the performance of the implemented clustering methods with different proximity measures and the number of clusters. In this way, the users will be able to choose an appropriate proximity function and the number of clusters to improve accuracy of clustering.