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. 2016 Jul 18;10:2323–2331. doi: 10.2147/DDDT.S110603

Table S2.

Five-fold cross validation model performance using experimental inactive agonists

Model CA SE SP AUC MCC
NB-ExtFP 0.7083 0.7247 0.6542 0.7385 0.3322
KNN-ExtFP 0.8425 0.9354 0.5327 0.7831 0.5219
RF-ExtFP 0.8035 0.9129 0.4393 0.7852 0.3966
SVM-ExtFP 0.8121 0.9522 0.3458 0.8275 0.3914
NB-MACCSFP 0.7169 0.7781 0.5140 0.7309 0.2715
KNN-MACCSFP 0.8186 0.9157 0.4953 0.7999 0.4517
RF-MACCSFP 0.8271 0.9298 0.4860 0.8141 0.4707
SVM-MACCSFP 0.8164 0.9522 0.3645 0.8083 0.4095
NB-PubChemFP 0.6305 0.6489 0.5701 0.6940 0.1883
KNN-PubChemFP 0.8380 0.9073 0.6075 0.7922 0.5312
RF-PubChemFP 0.7947 0.9326 0.3364 0.7969 0.3377
SVM-PubChemFP 0.7905 0.9382 0.2991 0.8057 0.3116
NB-AP2D 0.5376 0.5225 0.5888 0.5837 0.0938
KNN-AP2D 0.8098 0.8989 0.5140 0.7504 0.4380
RF-AP2D 0.7905 0.9944 0.1121 0.6727 0.2622
SVM-AP2D 0.7840 0.9860 0.1121 0.6324 0.2199

Abbreviations: NB, Naïve Bayesian; KNN, k-nearest neighbor; RF, random forest; SVM, support vector machine; Ext, extended; AP2D, 2D atom pairs; FP, fingerprints; SE, sensitivity; SP, specificity; AUC, area under the receiver operating characteristic curve; MCC, Matthews correlation coefficient; CA, classification accuracy.