Position Regularized Core Vector Machines

Shu Xia Lu; Cai Hong Jiao; Le Tong; Yang Fan Zhou

doi:10.4028/www.scientific.net/AMM.574.728

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 574Position Regularized Core Vector Machines

Position Regularized Core Vector Machines

Abstract:

Core Vector Machine (CVM) can be used to deal with large data sets by find minimum enclosing ball (MEB), but one drawback is that CVM is very sensitive to the outliers. To tackle this problem, we propose a novel Position Regularized Core Vector Machine (PCVM).In the proposed PCVM, the data points are regularized by assigning a position-based weighting. Experimental results on several benchmark data sets show that the performance of PCVM is much better than CVM.

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Periodical:

Applied Mechanics and Materials (Volume 574)

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728-733

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.574.728

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Online since:

July 2014

Authors:

Shu Xia Lu*, Cai Hong Jiao, Le Tong, Yang Fan Zhou

Keywords:

Core Set, Minimum Enclosing Ball, Support Vector Domain Description, Weighting

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