Kernel functions of SVM: A comparison and optimal solution

Abstract

Classification with better accuracy for all type of data set for a single classifiers is still a challenge in the domain of Machine learning. Improving the efficiency of classifiers is still a challenge for researchers. This notion has motivated to give comparative solution for the classifiers with the proposition of optimal solution. The classification algorithm can be applied for many application to improve its accuracy such as Gender and age classification, face etc. This is just to relinquish a boost to the svm algorithm researches in the various classification fields through the different kernel functions. The proposed methodology has propounded an optimal solution on the usage of kernel functions. There have been many researches on the kernel function comparisons. Here, a better and accurate solution has been applied on dataset for male female and transgender which is new gender has been classified and has been expectant to come up with a better accuracy.