@inproceedings{0e052ec9caa54f21b7e97657f19db97b,
title = "A speedup method for SVM decision",
abstract = "In this paper, we proposed a method to speed up the test phase of SVM based on Feature Vector Selection method (FVS). In the method, the support vectors (SVs) appeared in the decision function of SVM are replaced with some feature vectors (FVs) which are selected from support vectors by FVS method. Since it is a subset of SVs set, the size of FVs set is normally smaller than that of the SVs set, therefore the decision process of SVM is speeded up. Experiments on 12 datasets of IDA show that the number of SVs can be reduced from 20\% to 99\% with only a slight increase on the error rate of SVM by the proposed method. The trade-off between the generalization ability of obtained SVM and the speedup ability of the proposed method can be easily controlled by one parameter.",
author = "Yongsheng Zhu and Junyan Yang and Jian Ye and Youyun Zhang",
year = "2006",
doi = "10.1007/11815921\_54",
language = "英语",
isbn = "3540372369",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "494--501",
booktitle = "Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshops, SSPR 2006 and SPR 2006, Proceedings",
note = "Joint IAPR International Workshops on Structural, Syntactic, and Statistical Pattern Recognition, SSPR 2006 and SPR 2006 ; Conference date: 17-08-2006 Through 19-08-2006",
}