Correction for model selection bias using a modified model averaging approach for supervised learning methods applied to EEG experiments

摘要

This paper proposes a modified model averaging approach for linear discriminant analysis. This approach is used in combination with a doubly hierarchical supervised learning analysis and applied to preclinical pharmaco-electroencephalographical data for classification of psychotropic drugs. Classification of a test dataset was highly improved with this method.