Enhancing the Performance of Classifier Using Particle Swarm Optimization (PSO) - based Dimensionality Reduction
Danasingh Asir Antony Gnana Singh, Epiphany Jebamalar Leavline, K. Valliyappan, Mahesh Srinivasan · International Journal of Energy Information and Communications · 2015
Nowadays, the massive growth of data makes the data classification a challenging task.The feature selection is a demanding area to take this challenge and produce the higher accuracy in data classification by reducing the dimensionality of the data.Particle Swarm Optimization (PSO) is a computational technique which is applied in the feature selection process to get an optimal solution.This paper proposes a PSO and F-Score based feature selection algorithm for selecting the significant features that contribute to improve the classification accuracy.The performance of the proposed method is evaluated with various classifiers such as support vector machine (SVM), Naive Bayes, KNN and Decision Tree.The experimental results show that the proposed method outperforms the other methods compared.