Improved feature selection algorithm with conditional mutual information

Traditional feature selection algorithms have a common drawback, i.e. they do not consider the mutual relationships between features. It can result in that one feature's predictive power is weakened by others and the lost of efficiency. In this paper, we proposed a new feature selection method called Conditional Mutual Information Maximin (CMIM).It can select a set of individually discriminating and weakly dependent features. Simulation results demonstrate that the proposed method can improve the precision of text classification.