High-order conditional mutual information maximization for dealing with high-order dependencies in feature selection

•Mutual information feature selection method based on conditional mutual information.•Novel mutual information feature selection algorithm, exploring high order dependencies.•The proposed method allows seeing the mutual information feature selection with highorder dependencies with clear interpretation.•Compared with different methods over 20 benchmark datasets, the proposed method reached the best results.•The proposed method is faster and accurate than other feature selection methods that explore high order dependencies.