TY - GEN
T1 - A modified AdaBoost method for one-class SVM and its application to novelty detection
AU - CHEN, Xue-Fang
AU - XING, Hong-Jie
AU - WANG, Xi-Zhao
N1 - This work is partly supported by the National Natural Science Foundation of China (No. 60903089; 61073121), the China Postdoctoral Science Foundation (No. 20080440820), the Natural Science Foundation of Hebei Province (No. F2009000231), the Postdoctoral Science Foundation of Hebei University, and the Foundation of Hebei University (No. 2008123).
PY - 2011
Y1 - 2011
N2 - One-Class Support Vector Machine (OCSVM) is a general approach for novelty detection in the fields of machine learning and pattern classification. At the same time, AdaBoost is a famous ensemble method which can improve the performance of its base classifiers. However, the base classifiers in the AdaBoost method prefer to be weak classifiers. Since OCSVM is regarded as a strong classifier, the traditional AdaBoost method may not improve the classification performance of OCSVM. Therefore, to construct the AdaBoost method for OCSVM, we modify the traditional AdaBoost method to make it fit for OCSVM. Experimental results on three synthetic data sets and eight UCI benchmark data sets demonstrate that the proposed method is superior to its related methods.
AB - One-Class Support Vector Machine (OCSVM) is a general approach for novelty detection in the fields of machine learning and pattern classification. At the same time, AdaBoost is a famous ensemble method which can improve the performance of its base classifiers. However, the base classifiers in the AdaBoost method prefer to be weak classifiers. Since OCSVM is regarded as a strong classifier, the traditional AdaBoost method may not improve the classification performance of OCSVM. Therefore, to construct the AdaBoost method for OCSVM, we modify the traditional AdaBoost method to make it fit for OCSVM. Experimental results on three synthetic data sets and eight UCI benchmark data sets demonstrate that the proposed method is superior to its related methods.
KW - AdaBoost
KW - novelty detection
KW - OCSVM
UR - http://www.scopus.com/inward/record.url?scp=83755194768&partnerID=8YFLogxK
U2 - 10.1109/ICSMC.2011.6084212
DO - 10.1109/ICSMC.2011.6084212
M3 - Conference paper (refereed)
AN - SCOPUS:83755194768
SN - 9781457706530
T3 - IEEE International Conference on Systems, Man and Cybernetics
SP - 3506
EP - 3511
BT - Proceedings : 2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2011 : Conference Digest
PB - IEEE
T2 - 2011 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2011
Y2 - 9 October 2011 through 12 October 2011
ER -