Performance Evaluation of PSO Based Classifier for Classification of Multidimensional Data with Variation of PSO Parameters in Knowledge Discovery Database
In this paper, the authors have proposed a modified PSO based classification model for multidimensional real dataset and they 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 variations of parameters of the standard particle swarm optimizer. Here they 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 their proposed algorithm. They have also explored the possible influence of variants of PSO on accuracy of classification.