Table 6.

Model performance comparison on the original imbalanced dataset.

Model	Average accuracy	Average precision	Average recall	Average F1-score	Average AUROCa
LRb	0.92	0.69	0.14	0.24	0.57
NBc	0.85	0.25	0.35	0.29	0.62
RFd	0.90	0.42	0.15	0.22	0.57
XGBooste	0.92	0.70	0.15	0.24	0.57
AdaBoostf	0.92	0.70	0.14	0.23	0.57
MLPg	0.92	0.67	0.15	0.24	0.57
Sequential ANNh	0.92	0.64	0.14	0.23	0.57

^aAUROC: area under the receiver operating characteristic curve.

^bLR: logistic regression.

^cNB: naive Bayes.

^dRF: random forest.

^eXGBoost: extreme gradient boosting.

^fAdaBoost: adaptive boosting.

^gMLP: multilayer perceptron.

^hANN: artificial neural network.