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Table 5 Predictive performance of hybrid features for the four benchmark datasets

From: Prediction of HIV-1 protease cleavage site using a combination of sequence, structural, and physicochemical features

Features DT LR ANN
Acc.(%) AUC Acc.(%) AUC Acc.(%) AUC
746 Dataset
 Seq + Str 78.3 0.788 91.8 0.982 94.5 0.994 *
 Seq + Phy 83.7 0.838 86.4 0.968 94.5 0.976
 Phy + Str 83.7 0.810 78.3 0.860 91.8 0.982
 Seq + Str + Phy 75.6 0.841 97.2 0.991 97.2 0.988
1625 Dataset
 Seq + Str 89.0 0.910 96.3 0.980 95.1 0.992
 Seq + Phy 89.0 0.785 97.5 0.958 98.7 0.990
 Phy + Str 91.4 0.940 86.5 0.810 93.9 0.985
 Seq + Str + Phy 91.4 0.956 95.1 0.980 97.5 0.990
Schilling Dataset
 Seq + Str 90.8 0.845 86.5 0.865 92.0 0.873
 Seq + Phy 87.1 0.500 90.8 0.837 88.9 0.825
 Phy + Str 85.1 0.500 80.8 0.603 80.8 0.596
 Seq + Str + Phy 88.9 0.810 89.5 0.826 91.4 0.895
Impens Dataset
 Seq + Str 89.3 0.682 89.3 0.918 93.6 0.918
 Seq + Phy 91.4 0.839 87.2 0.889 91.4 0.896
 Phy + Str 85.1 0.500 82.9 0.889 93.6 0.932
 Seq + Str + Phy 87.2 0.675 87.2 0.889 89.3 0.850
  1. *The best accuracy and AUC in each dataset are underlined