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Table 1 10-Fold Cross-Validation performance on six datasets for KNN and SVM-L, λ1=0.5

From: Optimal selection of molecular descriptors for antimicrobial peptides classification: an evolutionary feature weighting approach

Dataset MLA Sens(%) Spec(%) Prec(%) Bal Acc(%) Acc(%) MCC AUC
DAMPD_AMP KNN 71.97 9 7 . 2 2 8 3 . 7 5 84.60 9 3 . 0 1 0 . 7 3 5 0.846
  SVM-L 8 8 . 0 7 a 92.30 69.56 9 0 . 1 9 91.62 0.734 0.902
APD3_AMP KNN 80.85 95.27 7 7 . 2 3 88.06 9 2 . 8 5 0.747 0.881
  SVM-L 9 1 . 6 5 92.53 70.75 9 2 . 0 9 92.36 0 . 7 6 2 0 . 9 2 1
DAMPD_ANTIBACTERIAL KNN 9 1 . 0 4 96.45 8 4 . 3 7 9 3 . 7 5 9 5 . 5 1 0 . 8 4 9 0 . 9 3 7
  SVM-L 88.49 9 6 . 5 4 84.18 92.51 95.06 0.832 0.925
APD3_ANTIBACTERIAL KNN 79.32 9 5 . 3 0 7 7 . 1 8 87.31 9 2 . 6 1 0.738 0.873
  SVM-L 9 1 . 3 4 92.22 70.33 9 1 . 7 8 92.07 0 . 7 5 6 0 . 9 1 8
DAMPD_BACTEROCIN KNN 100 95.53 85.83 97.76 96.36 0.902 0.978
  SVM-L 100 9 8 . 8 9 9 6 . 6 7 9 9 . 4 4 9 9 . 0 9 0 . 9 7 7 0 . 9 9 4
APD3_BACTEROCIN KNN 83.50 9 5 . 0 4 77.05 89.27 93.12 0.758 0.893
  SVM-L 8 5 . 3 8 94.83 7 7 . 2 8 9 0 . 1 0 93.12 0 . 7 6 8 0 . 9 0 1
  1. Each value is the average performance from 10-fold cross-validation by the classifier built by the machine learning algorithm (second column) on the dataset (first column). Wilcoxon signed rank test was performed on the measure resulting from the 10-fold cross-validation of KNN and SVM-L. The models with significant improvement at p-value ≤0.05 are marked with the symbol *
  2. aBold font indicates the best value per measure for every dataset