ISSN: 0970-938X (Print) | 0976-1683 (Electronic)

Biomedical Research

An International Journal of Medical Sciences


Abnormality detection using weighed particle swarm optimization and smooth support vector machine

In this paper, a new hybrid classification approach, which uses Weighted-Particle Swarm Optimization (WPSO) for data clustering in sequence with Smooth Support Vector Machine (SSVM) for classification is proposed. The performance of WPSO clustering is compared with K means and fuzzy methods using intercluster, intracluster and validity index. The accuracy of proposed WPSO-SSVM classification methodology are 83.76% for liver disorder, 98.42% for WBCD, 95.21% for mammographic mass data which are better than in existing literature.

Author(s): Latchoumi TP, Latha Parthiban
Abstract | Full-Text | PDF

Share this  Facebook  Twitter  LinkedIn  Google+