One way to improve accuracy of a classifier is to use the minimum number of features. Many
feature selection techniques are proposed to find out the most important features. In this
paper, feature selection methods Co-relation based feature Selection, Wrapper method and
Information Gain are used, before applying supervised learning based classification
techniques. The results show that Support vector Machine with Information Gain and
Wrapper method have the best results as compared to others tested.