Improved Feature Selection Algorithm Based on Conditional Mutual Information

Aiming at the shortcomings of traditional feature selection which are neglect of relevancy to the class and redundancy to the feature,this paper introduces a feature selection algorithm based on conditional mutual information.The algorithm clusters interdependent features into clusters and selects one feature which has maximum mutual information with class,the irrelevant and redundant features are removed.Experimental results show that the method is prior to traditional feature selection from the point of view of classification accuracy.