Predicting Prognostic Effects of Acupuncture for Depression Using the Electroencephalogram

Table 2

Hyperparameter configuration of machine learning methods.

Methods	Optimized hyperparameter settings
LR	Tolerance: ; solver:“Newton-cg”;
	Iterated epochs:100.
RF	No. of estimators:100; criterion = “gini”;
	Max features: “Sqrt”.
SVM-linear	kernel:“linear”; tolerance: .
SVM-poly	kernel:“poly”; tolerance: ; degree: 3.
SVM-RBF	kernel:“rbf”; tolerance: ;
	Gamma: “Scale”.