The Support Vector Machine (SVM) algorithm was firstly developed in 1963 by Vapnik and Lerner. SVM [7] [12] is a two class classifier based on supervised learning which gives better result than other classifiers. SVM classifies between two classes by constructing a hyperplane in high-dimensional feature space which can be used for classification. SVM is a classification algorithm based on kernel methods. SVM is classified in two groups.