MIFS-ND: A mutual information-based feature selection method
We propose a greedy feature selection method using mutual information theory. The method uses featureclass and featurefeature mutual information. We use NSGA-II method to select an optimal feature subset. The accuracy of the proposed method is evaluated using multiple classifiers.
mutual information features relevance classification