(A) The correlation between every feature vector in the training data and the corresponding label based on chi-square statistics. (B) The AUC value of 10-fold cross-validation with the decrease of feature dimension. (C) The t-distributed Stochastic Neighbor Embedding (t-SNE) visualization of the benchmark data set in a 2D feature space before and after feature optimization.