SVM : Support vector machine

The support vector machine is base on the idea of finding the best line or hyperplane that distinctly classifies the data point. SVM can find the best hyperplane in N- dimensions. Here N is the number of features. For example, if you have two features: A, B then the hyperplane is just a line and if there is three features: A, B, and C, your points will be plotted in the corresponding three-dimensional space based on their values for each independent variable. Support vector machine is a powerful supervised machine learning algorithm. It is used for both classification and regression problems.