A review of the most common partition algorithms in cluster analysis: A comparative study Una revisión de los algoritmos de partición más comunes en el análisis de conglomerados: Un estudio comparativo

Leiva-Valdebenito S.A.; Torres-Avilés, F.J.

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.

Más información

Título de la Revista: Revista Colombiana de Estadística
Volumen: 33
Número: 2
Editorial: Departamento de Estadística - Universidad Nacional de Colombia.
Fecha de publicación: 2010
Página de inicio: 321
Página final: 339
URL: http://www.scopus.com/inward/record.url?eid=2-s2.0-79955795592&partnerID=q2rCbXpz