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영어

In this paper we have proposed a modified PSO based classification model for multidimensional real dataset and we have studied the results of experiment by implementing particle swarm optimization in classification. Evaluation of the performance of PSO based classifier has been made by considering several variation of parameters of the standard particle swarm optimizer. Here we have used a multidimensional real cancer dataset for classification using PSO to study the behavior of PSO parameters and to observe the accuracy of classification of PSO based classifier in different iterations. Extensive simulation has been carried out using UCI data, on which classification is done using our proposed algorithm. We have also explored the possible influence of variants of PSO on accuracy of classification. The obtained results indicate that particle swarm optimization is an effective technique for classification and can be used successfully on more demanding problem domain.