Support Vector Data Description: Means of Detecting Artificially-Induced Postural Degradation, machine learning, biomedical signal processing - Couverture souple

Srivastava, Chandan

 
9783844385212: Support Vector Data Description: Means of Detecting Artificially-Induced Postural Degradation, machine learning, biomedical signal processing
Couverture souple
ISBN 10 : 3844385215 ISBN 13 : 9783844385212
Editeur : LAP LAMBERT Academic Publishing, 2011

Synopsis

This book is based on the basis that machine learningalgorithms and rank based statistical methods are abetter choice to develop a robust model in logicalsituations. We designed experimental setup for datacollection, developed unique class of model includingvariable selection, and detection methods. Theselected significant variables provide a unique classof model for all six participants. We emphasize thebest selected variables have good information formodel development, and each selected variable have noerror i.e.; AUC=1, with forward selection and supportvector data description classifier. Basically, wedeveloped a unique class of model using six differentclasses of subjects, predicting elderly fallprevention, and after doing external validation withseventh class of subject, we reached a uniquesolution. Sections one is research introduction,section two is all about research design and dataanalysis, section three and four give extensivedevelopment of model for variable selection and oneclass classifier. Then finally given the conclusionand future aspect of whole study.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

This book is based on the basis that machine learningalgorithms and rank based statistical methods are abetter choice to develop a robust model in logicalsituations. We designed experimental setup for datacollection, developed unique class of model includingvariable selection, and detection methods. Theselected significant variables provide a unique classof model for all six participants. We emphasize thebest selected variables have good information formodel development, and each selected variable have noerror i.e.; AUC=1, with forward selection and supportvector data description classifier. Basically, wedeveloped a unique class of model using six differentclasses of subjects, predicting elderly fallprevention, and after doing external validation withseventh class of subject, we reached a uniquesolution. Sections one is research introduction,section two is all about research design and dataanalysis, section three and four give extensivedevelopment of model for variable selection and oneclass classifier. Then finally given the conclusionand future aspect of whole study.

Biographie de l'auteur

Chandan Srivastava is doctoral research fellow at Department deEnginyeria Química, Universitat Rovira i Virgili,Spain. He hasobtained his master study and research at the Department ofSystem Optimization and Security, University of Technology ofTroyes,France. His area of research includes machinelearning, and biomedical signal processing.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2011
Langue
anglais
ISBN 10 
3844385215
ISBN 13 
9783844385212
Reliure
Broché
Nombre de pages
72
Coordonnées du fabricant
non disponible
Personne responsable
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