Feature selection using feature distinguishability and discernibility object pair set
Zhou Rui-qiong · Computer Engineering and Applications Journal · 2010
Feature selection is one of the key steps in text categorization.The selected feature subset directly influences results of text categorization.Firstly,several classic feature selection methods are analyzed simply and their deficiencies are summarized.And then,the concept of feature distinguishability is presented.Next,an attribute reduction algorithm based on discernibility object pair set is provided.Finally,combining the attribute reduction algorithm with feature distinguishability,a new feature selection method is proposed.The new method firstly uses feature distinguishability to select feature and filter out some terms to reduce the sparsity of feature spaces,and then employs the attribute reduction algorithm to eliminate redundancy,so that the feature subsets which are more representative are acquired.The experimental results show that the new method is promising.