A novel margin based algorithm for feature extraction

doi:10.1007/s00354-009-0066-z

CORC > 北京大学 > 信息科学技术学院

	A novel margin based algorithm for feature extraction
	Yang, Cheng ; Wang, Liwei ; Feng, Jufu
刊名	New Generation Computing
	2009
DOI	10.1007/s00354-009-0066-z
英文摘要	Margin based feature extraction has become a hot topic in machine learning and pattern recognition. In this paper, we present a novel feature extraction method called Adaptive Margin Maximization (AMM) in which margin is defined to measure the discrimination ability of the features. The motivation comes principally from the iterative weight modification mechanism of the powerful boosting algorithms. In our AMM, the samples are dynamically weighted and features are learned sequentially. After one new feature is learned by maximizing the weighted total margin of data, the weights are updated so that the samples with smaller margins receive larger weights. The feature learned in the next round will thus try to concentrate more on these 'hard' samples adaptively. We show that when the data are projected onto the feature space learned by AMM, most examples have large margins, and therefore the nearest neighbor classifier yields small generalization error. This is in contrast to existing margin maximization based feature extraction approaches, in which the goal is to maximize the total margin. Extensive experimental results on benchmark datasets demonstrate the effectiveness of our method.; EI; 4; 285-305; 27
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/460924]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Yang, Cheng,Wang, Liwei,Feng, Jufu. A novel margin based algorithm for feature extraction[J]. New Generation Computing,2009.
APA	Yang, Cheng,Wang, Liwei,&Feng, Jufu.(2009).A novel margin based algorithm for feature extraction.New Generation Computing.
MLA	Yang, Cheng,et al."A novel margin based algorithm for feature extraction".New Generation Computing (2009).