From: Predicting combinations of drugs by exploiting graph embedding of heterogeneous networks
Classifier | Accuracy | Precision | Recall | F-measure | MCC | AUC |
---|---|---|---|---|---|---|
SVM | 0.751 | 0.566 | 0.635 | 0.751 | 0.436 | 0.753 |
KNN | 0.736 | 0.471 | 0.489 | 0.727 | 0.371 | 0.673 |
LDA | 0.743 | 0.486 | 0.540 | 0.738 | 0.397 | 0.691 |
ADB | 0.746 | 0.490 | 0.540 | 0.741 | 0.404 | 0.693 |
GBT | 0.741 | 0.480 | 0.516 | 0.734 | 0.387 | 0.683 |
RF | 0.732 | 0.465 | 0.486 | 0.723 | 0.361 | 0.668 |
LR | 0.741 | 0.479 | 0.510 | 0.733 | 0.385 | 0.681 |