A stacking ensemble of KNN, SVM, MLP, and AdaBoost with logistic regression reports 98.75% accuracy for depression classification, but the experimental protocol raises leakage concerns.
Predicting anxiety, depression and stress in modern life using machine learning algorithms,
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A Model-Mediated Stacked Ensemble Approach for Depression Prediction Among Professionals
A stacking ensemble of KNN, SVM, MLP, and AdaBoost with logistic regression reports 98.75% accuracy for depression classification, but the experimental protocol raises leakage concerns.