Simultaneous Clustering and Model Selection for Multinomial Distribution: A Comparative StudyReportar como inadecuado




Simultaneous Clustering and Model Selection for Multinomial Distribution: A Comparative Study - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

1 ERIC - Equipe de Recherche en Ingénierie des Connaissances 2 MODAL - MOdel for Data Analysis and Learning Inria Lille - Nord Europe, LPP - Laboratoire Paul Painlevé, CERIM - Santé publique : épidémiologie et qualité des soins-EA 2694, Polytech Lille, Université de Lille 1, IUT’A

Abstract : In this paper, we study different discrete data clustering methods, which use the Model-Based Clustering MBC framework with the Multinomial distribution. Our study comprises several relevant issues, such as initialization, model estimation and model selection. Additionally, we propose a novel MBC method by efficiently combining the partitional and hierarchical clustering techniques. We conduct experiments on both synthetic and real data and evaluate the methods using accuracy, stability and computation time. Our study identifies appropriate strategies to be used for discrete data analysis with the MBC methods. Moreover, our proposed method is very competitive w.r.t. clustering accuracy and better w.r.t. stability and computation time.





Autor: Md Abul Hasnat - Julien Velcin - Stéphane Bonnevay - Julien Jacques -

Fuente: https://hal.archives-ouvertes.fr/



DESCARGAR PDF




Documentos relacionados