Table 3.

Performance summary of six machine learning models of HT.

Models	Accuracy	Precision	Recall	F1 Score	AUC Score
KNN	0.681029	0.746247	0.681507	0.710569	0.728307
LR	0.701378	0.730701	0.780822	0.749290	0.767496
SVM	0.710839	0.720756	0.825304	0.766319	0.766069
DT	0.643135	0.680359	0.706202	0.691899	0.633101
MLP	0.721863	0.746918	0.797603	0.767313	0.775333
XGBoost	0.729774	0.770717	0.772755	0.767228	0.781673

AUC, area under curve; KNN, k-nearest neighbor classifier; LR, logistic regression; SVM, a support vector machine; DT, the decision tree model; MLP, the multilayer perceptron network; XGBoost, eXtreme Gradient Boosting.