Methods |
F1-Score |
Sensitivity |
Precision |
Specificity |
Hamming
Loss |
Accuracy |
G-Mean |
AUC |
ARF-OOBEE |
0.9022±0.0098 |
0.8949±0.0118 |
0.9151±0.0165 |
0.9805±0.0338 |
0.0296±0.0055 |
0.9704±0.0168 |
0.9367±0.0138 |
0.9830±0.0202 |
GcForest |
0.9140±0.0145 |
0.8980±0.0144 |
0.9420±0.0169 |
0.9810±0.0392 |
0.0252±0.0078 |
0.9748±0.0210 |
0.9386±0.0236 |
0.9528±0.0214 |
LR |
0.8052±0.0136 |
0.7905±0.0110 |
0.8622±0.0160 |
0.9581±0.0300 |
0.0520±0.0079 |
0.9480±0.0196 |
0.8703±0.0210 |
0.9616±0.0225 |
NaiveBayes |
0.7587±0.0148 |
0.8085±0.0106 |
0.7404±0.0130 |
0.9113±0.0380 |
0.0962±0.038 |
0.9038±0.0213 |
0.8584±0.0220 |
0.9153±0.0222 |
MLP |
0.7673±0.0152 |
0.7532±0.0126 |
0.8327±0.0165 |
0.9409±0.0099 |
0.0745±0.0380 |
0.9255±0.0226 |
0.8418±0.0232 |
0.9070±0.0236 |
SVM |
0.7411±0.0133 |
0.7949±0.0119 |
0.7137±0.0135 |
0.8941±0.0333 |
0.1090±0.0083 |
0.8910±0.0212 |
0.8430±0.0231 |
0.8789±0.0230 |
XGBoost |
0.8804±0.0116 |
0.8552±0.0114 |
0.9435±0.0176 |
0.9725±0.0353 |
0.0335±0.0079 |
0.9665±0.0185 |
0.9120±0.0227 |
0.9726±0.0189 |