NFL-SVM: An Effective Algorithm for Solving Misclassification in SVM

Considering the problem of low classification accuracy of similar category, this paper proposes NFL- SVM, an effective algorithm for solving misclassification in SVM. By analysis and deduction, this paper indicates that SVM can be considered the nearest neighbor classifier of just one feature point in each category. KNFL regards lines of all points as feature lines, so it can be used to overcome defaults in SVM. The results of experiment at last show us that NFL-SVM can provide a better performance in classification accuracy.