Figure 3

Mean AUROC values for classifiers obtained with 20 selected features (3-fold CV). NB, Gaussian Naive Bayes; KNN, k-nearest neighbors algorithm; LDA, linear discriminant analysis; SVM linear, support vector machine linear; LR, logistic regression; MLP, multilayer perceptron; DT, decision tree; RF, random forest; XGB, XGBoost; AdaB, AdaBoost classifier; Bagging, Bagging classifier; AC, amino acid composition; APAAC, amphiphilic pseudo-amino acid composition; DC, di-amino acid composition; MB, Moreau-Broto autocorrelation; Mix, total descriptors; TC, tri-amino acid composition.