No abstract

In data mining, the reduction of dimension is a highly complicated process, and it should be processed in an efficient way to get an optimal solution. So in this paper, the fuzzy rough set theory is implemented for optimal feature selection in the normalized data of KDD cup 99 datasets. The Nash equilibrium game theory is fed as an input to update the kernel on SVM. The Nash equilibrium gives the rapid update and provides an accurate rate of classification in data reduction. The performance values computed for this method is measured in terms of accuracy, precision, detection rate, F-score, FPR and AUC.