PSO - SVM based classifiers: A comparative approach

Abstract

Evolutionary and natural computing techniques have been drawn considerable interest for analyzing large datasets with large number of features. Various flavors of Particle Swarm Optimization (PSO) have been applied in the various research applications like Control and Automation, Function Optimization, Dimensionality Reduction, classification. In the present work, we have applied the SVM based classifier along with Novel PSO and Binary PSO on Huesken dataset of siRNA features as well as on nine other benchmark dataset and achieved results are quite satisfactory. The results of our study have been compared with other results available in the literature. © 2010 Springer-Verlag Berlin Heidelberg.