TY - GEN
T1 - Adaptive weighted fusion of local kernel classifiers for effective pattern classification
AU - Yang, Shixin
AU - Zuo, Wangmeng
AU - Liu, Lei
AU - Li, Yanlai
AU - Zhang, Dapeng
PY - 2011/12/1
Y1 - 2011/12/1
N2 - The theoretical and practical virtual of local learning algorithms had been verified by the machine learning community. The selection of the proper local classifier, however, remains a challenging problem. Rather than selecting one single local classifier, in this paper, we propose to choose several local classifiers and use adaptive fusion strategy to alleviate the choice problem of the proper local classifier. Based on the fast and scalable local kernel support vector machine (FaLK-SVM), we adopt the self-adaptive weighting fusion method for combining local support vector machine classifiers (FaLK-SVMa), and provide two fusion methods, distance-based weighting (FaLK-SVMad) and rank-based weighting methods (FaLK-SVMar). Experimental results on fourteen UCI datasets and three large scale datasets show that FaLK-SVMa can chieve higher classification accuracy than FaLK-SVM.
AB - The theoretical and practical virtual of local learning algorithms had been verified by the machine learning community. The selection of the proper local classifier, however, remains a challenging problem. Rather than selecting one single local classifier, in this paper, we propose to choose several local classifiers and use adaptive fusion strategy to alleviate the choice problem of the proper local classifier. Based on the fast and scalable local kernel support vector machine (FaLK-SVM), we adopt the self-adaptive weighting fusion method for combining local support vector machine classifiers (FaLK-SVMa), and provide two fusion methods, distance-based weighting (FaLK-SVMad) and rank-based weighting methods (FaLK-SVMar). Experimental results on fourteen UCI datasets and three large scale datasets show that FaLK-SVMa can chieve higher classification accuracy than FaLK-SVM.
KW - classifier fusion
KW - Kernel method
KW - local learning
KW - nearest neighbors
KW - support vector machine
UR - http://www.scopus.com/inward/record.url?scp=84863131561&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-24728-6_9
DO - 10.1007/978-3-642-24728-6_9
M3 - Conference article published in proceeding or book
SN - 9783642247279
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 63
EP - 70
BT - Advanced Intelligent Computing - 7th International Conference, ICIC 2011, Revised Selected Papers
T2 - 7th International Conference on Intelligent Computing, ICIC 2011
Y2 - 11 August 2011 through 14 August 2011
ER -