SVM-Based Local Search for Gene Selection and Classification of Microarray Data

TitreSVM-Based Local Search for Gene Selection and Classification of Microarray Data
Type de publicationCommunication
TypeCommunication avec actes dans un congrès
Année2008
LangueAnglais
Date du colloque2008
Titre du colloqueSecond International Conference, BIRD 2008
Titre des actes ou de la revueBioinformatics Research and Development
Volume13
Pagination499 - 508
AuteurHernandez, Jose Crispin He, Duval, Béatrice , Hao, Jin-Kao
PaysAutriche
EditeurSpringer
VilleVienne
ISBN978-3-540-70598-7 / 978-3-540-70600-7
Mots-clésbioinformatics, Computational Biology/Bioinformatics, Feature selection, Local search, Microarray gene expression, Support vector machines
Résumé en anglais

This paper presents a SVM-based local search (SVM-LS) approach to the problem of gene selection and classification of microarray data. The proposed approach is highlighted by the use of a SVM classifier both as an essential part of the evaluation function and as a “provider” of useful information for designing effective LS algorithms. The SVM-LS approach is assessed on a set of three well-known data sets and compared with some best algorithms from the literature.

Notes

Date du colloque : 07/2008

URL de la noticehttp://okina.univ-angers.fr/publications/ua4463
DOI10.1007/978-3-540-70600-7_39
Lien vers le document en ligne

http://link.springer.com/chapter/10.1007/978-3-540-70600-7_39