Machine Learning-Based Forecast of Hemorrhagic Stroke Healthcare Service Demand considering Air Pollution

Table 8

The values of the t-test between models with and without considering air pollution regarding different metrics.

	XGBTree	XGBLinear	LR	KNN	SVMLinear	RF
AUC	0.2114	0.3777	0.0316	0.969	0.3872	0.6214
Sensitivity	0.7939	0.0748	0.2558	0.2202	0.267	0.5365
Specificity	0.1211	0.1897	0.2148	0.4136	0.0004	0.5913

0.001, 0.01, and 0.05. LR, logistic regression; RF, random forest; SVMLinear, support-vector machines with linear kernel; KNN, k-nearest neighbor algorithm; XGBTree, extreme gradient boosting decision tree; XGBLinear, extreme gradient boosting linear model.