Support Vector Machine, Support Vector Classifier, Kernel Trick, Rbf, Polynomial.
ϵ = the error we have allowed to make some amount of misclassification, C = maximum value of summation of all errors(ϵ). Here extra higher dimensional term is be added due to kernel projection. So the parameters of SVM to be tuned are hereby as following : Kernel ( to increase the model accuracy) C