PLS discriminant analysis for functional data
Document type :
Communication dans un congrès avec actes
Title :
PLS discriminant analysis for functional data
Author(s) :
Preda, Cristian [Auteur]
Faculté de Médecine Henri Warembourg - Université de Lille
MOdel for Data Analysis and Learning [MODAL]
Saporta, Gilbert [Auteur]
CEDRIC. Méthodes statistiques de data-mining et apprentissage [CEDRIC - MSDMA]
Faculté de Médecine Henri Warembourg - Université de Lille
MOdel for Data Analysis and Learning [MODAL]
Saporta, Gilbert [Auteur]
CEDRIC. Méthodes statistiques de data-mining et apprentissage [CEDRIC - MSDMA]
Conference title :
ASMDA'05 XIth Int. Symp. on Applied Stochastic Models and Data Analysis
City :
Brest
Country :
France
Start date of the conference :
2005-05-17
Publication date :
2005-01-01
HAL domain(s) :
Mathématiques [math]/Statistiques [math.ST]
English abstract : [en]
Partial least squares regression on functional data is applied in thecontext of linear discriminant analysis with binary response. The discriminant coefficient function is then used to compute score to one of the two ...
Show more >Partial least squares regression on functional data is applied in thecontext of linear discriminant analysis with binary response. The discriminant coefficient function is then used to compute score to one of the two classes. The method is applied to gait data and the results are compared with those given by linear discriminant analysis and logistic regression on the principal components of predictors.Show less >
Show more >Partial least squares regression on functional data is applied in thecontext of linear discriminant analysis with binary response. The discriminant coefficient function is then used to compute score to one of the two classes. The method is applied to gait data and the results are compared with those given by linear discriminant analysis and logistic regression on the principal components of predictors.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Non spécifiée
Popular science :
Non
Collections :
Source :
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