Notes about the paper entitled “A hybridized K-means clustering approach for high dimensional dataset”

Arriaza-Gómez, AJ; Fernández-Palacin, F; Muñoz-Marquez, M; Pérez-Plaza, SM

doi:10.4314/IJEST.V6I1.2

Notes about the paper entitled “A hybridized K-means clustering approach for high dimensional dataset”

1 Department of Statistics and Operations Research, University of Cádiz, Spain

Revista:

International Journal of Engineering, Science and Technology

ISSN: 2141-2839, 2141-2820

Año de publicación: 2014

Volumen: 6

Número: 1

Páginas: 20-26

Tipo: Artículo

DOI: 10.4314/IJEST.V6I1.2 GOOGLE SCHOLAR Acceso abierto editor

Otras publicaciones en: International Journal of Engineering, Science and Technology

Resumen

In the paper “A hybridized K-means clustering approach for high dimensional dataset” Dash, Mishra, Rash and Acharya have presented a new version of the k-means algorithm. In it, principal components analysis (PCA) was used before applying the kmeans algorithm with a new initialization method. The authors compare the results obtained by using the HKMCA and PCA with the results of the original k-means, but a direct comparison is not valid as this paper shows.