Faster and more robust point symmetry-based K-means algorithm

Authors:
Kuo-Liang Chung;Jhin-Sian Lin
Affiliations:
Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei, Taiwan 10672, ROC;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei, Taiwan 10672, ROC
Venue:
Pattern Recognition
Year:
2007

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Abstract

Based on the recently published point symmetry distance (PSD) measure, this paper presents a novel PSD measure, namely symmetry similarity level (SSL) operator for K-means algorithm. Our proposed modified point symmetry-based K-means (MPSK) algorithm is more robust than the previous PSK algorithm by Su and Chou. Not only the proposed MPSK algorithm is suitable for the symmetrical intra-clusters as the PSK algorithm does, the proposed MPSK algorithm is also suitable for the symmetrical inter-clusters. In addition, two speedup strategies are presented to reduce the time required in the proposed MPSK algorithm. Experimental results demonstrate the significant execution-time improvement and the extension to the symmetrical inter-clusters of the proposed MPSK algorithm when compared to the previous PSK algorithm.