Set | Method | Predicted Compounds | Correctly Predicted | MCC | 5-Fold CV | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
TP | FP | TN | FN | |||||||||||
% | ||||||||||||||
Training set | SVMD | 74 | 26 | 79 | 21 | 77 | 0.54 | |||||||
Training set | SVME | 79 | 21 | 84 | 16 | 82 | 0.63 | |||||||
Training set | RF | 100 | 0 | 100 | 0 | 100 | 1.00 | |||||||
Training set | kNN | 86 | 14 | 80 | 20 | 83 | 0.66 | |||||||
Training set | C4.5/J48 | 98 | 02 | 97 | 02 | 97 | 0.95 | |||||||
Test set | SVMD | 73 | 27 | 73 | 27 | 73 | 0.46 | |||||||
Test set | SVME | 73 | 27 | 78 | 22 | 75 | 0.51 | |||||||
Test set | RF | 78 | 22 | 74 | 26 | 76 | 0.52 | |||||||
Test set | kNN | 79 | 21 | 68 | 32 | 74 | 0.47 | |||||||
Test set | C4.5/J48 | 71 | 29 | 70 | 30 | 71 | 0.41 |
|
TP, number of true positives; FP, number of false positives; TN, number of true negatives; FN, number of false negatives; MCC, Matthews correlation coefficient; CV, cross-validation; SVMD, support vector machine, linear model; SVME, support vector machine, nonlinear model; RF, random forest method; kNN, kappa nearest neighbors method; C4.5/J48, decision tree method.