A New Method for Feature Subset Selection for Handling Classification Problems

In this paper, we present a new method for dealing with feature subset selection for handling classification problems. We discriminate numeric features to construct the membership function of each fuzzy subset of each feature. Then, we select the feature subset based on the proposed fuzzy entropy measure with boundary samples. The proposed feature subset selection method cam select relevant features from sample data to get higher average classification accuracy rates than the ones selected by the existing methods