TY - GEN
T1 - Nearest mean classification via one-class SVM
AU - Shin, Donghyuk
AU - Kim, Saejoon
N1 - Copyright:
Copyright 2009 Elsevier B.V., All rights reserved.
PY - 2009
Y1 - 2009
N2 - We propose a new multi-class classification algorithm based on one-class SVM and nearest mean classifier methods. A wrapper-style feature selection scheme designed specifically for our algorithm is also provided for increased classification accuracy. It will be demonstrated that the proposed classification algorithm provide excellent performance, and in particular, performs strictly better than some of the currently known best classification algorithms on five biological datasets.
AB - We propose a new multi-class classification algorithm based on one-class SVM and nearest mean classifier methods. A wrapper-style feature selection scheme designed specifically for our algorithm is also provided for increased classification accuracy. It will be demonstrated that the proposed classification algorithm provide excellent performance, and in particular, performs strictly better than some of the currently known best classification algorithms on five biological datasets.
UR - http://www.scopus.com/inward/record.url?scp=70649097037&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70649097037&partnerID=8YFLogxK
U2 - 10.1109/CSO.2009.388
DO - 10.1109/CSO.2009.388
M3 - Conference contribution
AN - SCOPUS:70649097037
SN - 9780769536057
T3 - Proceedings of the 2009 International Joint Conference on Computational Sciences and Optimization, CSO 2009
SP - 593
EP - 596
BT - Proceedings of the 2009 International Joint Conference on Computational Sciences and Optimization, CSO 2009
T2 - 2009 International Joint Conference on Computational Sciences and Optimization, CSO 2009
Y2 - 24 April 2009 through 26 April 2009
ER -