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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/11001

Title: Correction for Model Selection Bias Using a Modified Model Averaging Approach for Supervised Learning Methods Applied to EEG Experiments
Authors: WOUTERS, Kristien
CORTINAS ABRAHANTES, Jose
MOLENBERGHS, Geert
GEYS, Helena
Bijnens, L.
Ahnaou, Abdellah
Drinkenburg, W.H.I.M.
Issue Date: 2010
Publisher: TAYLOR & FRANCIS INC
Citation: JOURNAL OF BIOPHARMACEUTICAL STATISTICS, 20 (4). p. 768-786
Abstract: 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.
Notes: [Wouters, Kristien; Abrahantes, Jose Cortinas; Molenberghs, Geert; Geys, Helena] Univ Hasselt, Interuniv Inst Biostat & Stat Bioinformat, Diepenbeek, Belgium. [Geys, Helena; Ahnaou, Abdellah; Drinkenburg, Wilhelmus H. I. M.; Bijnens, Luc] Johnson & Johnson Pharmaceut Res & Dev, Beerse, Belgium. wouters.kristien@gmail.com
URI: http://hdl.handle.net/1942/11001
DOI: 10.1080/10543401003618744
ISI #: 000278003200005
ISSN: 1054-3406
Category: A1
Type: Journal Contribution
Validation: ecoom, 2011
Appears in Collections: Research publications

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