A REVIEW OF THE MOST COMMON PARTITION ALGORITHMS IN CLUSTER ANALYSIS: A COMPARATIVE STUDY

Abstract

This study is oriented to compare several partition methods in the context of cluster analysis, which are also called non hierarchical methods. In this work, a simulation study is performed to compare the results obtained from the implementation of the algorithms k-means, k-medians, PAM and CLARA when continuous multivariate information is available. Additionally, a study of simulation is presented to compare partition algorithms qualitative information, comparing the efficiency of the PAM and k-modes algorithms. The efficiency of the algorithms is compared using the Adjusted Rand Index and the correct classification rate. Finally, the algorithms are applied to real databases with predefined classes.