Titre du document / Document title
Using domain knowledge in the random subspace method : Application to the classification of biomedical spectra
Auteur(s) / Author(s)
PRANCKEVICIENE Erinija (1 2) ;
BAUMGARTNER Richard (1) ;
SOMORJAI Ray (1) ;
Affiliation(s) du ou des auteurs / Author(s) Affiliation(s)
(1) Institute for Biodiagnostics, National Research Council Canada, 435 Ellice Avenue, Winnipeg, CANADA
(2) Kaunas University of Technology, Studentu 50, Kaunas, LITUANIE
Résumé / Abstract
Spectra intrinsically possess domain knowledge, making possible a domain-based feature selection model. The random subspace method, in combination with domain-knowledge-based feature sets, leads to improved classification accuracies in real-life biomedical problems. Using such feature sets allows for an efficient reduction of dimensionality, while preserving interpretability of classification outcomes, important for the field expert. We demonstrate the utility of domain knowledge-based features for the random subspace method for the classification of three real-life high-dimensional biomedical magnetic resonance (MR) spectra.
Revue / Journal Title
Lecture notes in computer science
ISSN
0302-9743
Source / Source
Congrès
MCS 2005 : multiple classifier systems :
(
Seaside CA, 13-15 June 2005
)
Multiple classifier systems. International workshop N
o6, Seaside CA
, ETATS-UNIS
(13/06/2005)
2005
, vol. 3541, pp. 336-345[Note(s) : XII, 430 p., ] [Document : 10 p.] (16 ref.)
ISBN 3-540-26306-3 ;
Illustration : Illustration
;
Langue / Language
Anglais
Editeur / Publisher
Springer, Berlin, ALLEMAGNE
(1973)
(Revue)
Springer, Berlin, ALLEMAGNE
(2005)
(Monographie)
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Localisation / Location
INIST-CNRS, Cote INIST : 16343, 35400012448743.0340
Nº notice refdoc (ud4) : 16923043