QQ客服 官方微博 反馈留言

	An imbalanced training data SVM classification problem based on Riemannian metric
	Zhou Qifeng ; Lin Chengde ; Luo Linkai ; Peng Hong ; Cheng, DZ ; Wu, M ; Lin CD(林成德)
	2007
关键词	imbalance classification support vector machine kernel function Riemannian metric
英文摘要	A method based on Riemannian metric to the classification problem with imbalanced training data was proposed. The idea is based on the analysis of the optimizing hyper-plane and support vectors induced by an RBF kernel. We use the conformal transformation and Riemannian metric to modify this RBF kernel, and reconstruct a new SVM with the modified kernel. The later SVM is shown to be superior to the traditional SVM classifier. Experimental results show that this method can improve the accuracy of the class with less training data under a high total accuracy.
语种	英语
内容类型	期刊论文
源URL	[http://dspace.xmu.edu.cn/handle/2288/70966]
专题	信息技术－已发表论文
推荐引用方式 GB/T 7714	Zhou Qifeng,Lin Chengde,Luo Linkai,et al. An imbalanced training data SVM classification problem based on Riemannian metric[J],2007.
APA	Zhou Qifeng.,Lin Chengde.,Luo Linkai.,Peng Hong.,Cheng, DZ.,...&林成德.(2007).An imbalanced training data SVM classification problem based on Riemannian metric..
MLA	Zhou Qifeng,et al."An imbalanced training data SVM classification problem based on Riemannian metric".(2007).

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。