Construction and validation of machine learning algorithm for predicting depression among home-quarantined individuals during the large-scale COVID-19 outbreak: based on Adaboost model

Table 3 Evaluation of the learning performance of the adaboost model with default parameters and after optimization of the parameters

10-fold cross- validation	Accuracy	AUC	Recall	Precision	F1-score	Kappa	MCC
Adaboost^a	0.7894	0.7767	0.5484	0.7056	0.6049	0.4656	0.4799
Adaboost^b	0.7917	0.7803	0.5275	0.7180	0.5977	0.4630	0.4793

ISSN: 2050-7283