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Santana, Roberto and Larrañaga Múgica, Pedro María and Bielza Lozoya, Maria Concepcion (2012). Regularized logistic regression and multi-objective variable selection for classifying MEG data. "Biological Cybernetics", v. 106 (n. 6-7); pp. 389-405. ISSN 0340-1200. https://doi.org/10.1007/s00422-012-0506-6.
Title: | Regularized logistic regression and multi-objective variable selection for classifying MEG data |
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Author/s: |
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Item Type: | Article |
Título de Revista/Publicación: | Biological Cybernetics |
Date: | September 2012 |
ISSN: | 0340-1200 |
Volume: | 106 |
Subjects: | |
Freetext Keywords: | Brain computer interface, Interfaz cerebro-ordenador, MEG, Multiobjective optimization, Optimización multiobjetivo, Classification, Clasificación, Feature subset selection, Selección de características del subconjunto, Probabilistic modeling, Modelo probabilístico. |
Faculty: | Facultad de Informática (UPM) |
Department: | Inteligencia Artificial |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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This paper addresses the question of maximizing classifier accuracy for classifying task-related mental activity from Magnetoencelophalography (MEG) data. We propose the use of different sources of information and introduce an automatic channel selection procedure. To determine an informative set of channels, our approach combines a variety of machine learning algorithms: feature subset selection methods, classifiers based on regularized logistic regression, information fusion, and multiobjective optimization based on probabilistic modeling of the search space. The experimental results show that our proposal is able to improve classification accuracy compared to approaches whose classifiers use only one type of MEG information or for which the set of channels is fixed a priori.
Item ID: | 16447 |
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DC Identifier: | https://oa.upm.es/16447/ |
OAI Identifier: | oai:oa.upm.es:16447 |
DOI: | 10.1007/s00422-012-0506-6 |
Official URL: | http://link.springer.com/article/10.1007%2Fs00422-012-0506-6 |
Deposited by: | Memoria Investigacion |
Deposited on: | 15 Jul 2013 15:01 |
Last Modified: | 21 Apr 2016 16:45 |