Presentation	2007-03-14 On Variable Selection in Decomposition Methods for Support Vector Machines : Proposal and Experimental Evaluation of a Novel Variable Selection based on Conjugate Gradient Method Yusuke KAWAZOE, Masashi KURANOSHITA, Norikazu TAKAHASHI, Jun-ichi TAKEUCHI,
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Abstract(in English)	Learning of a support vector machine (SVM) is formulated as a quadratic programming (QP) problem. Decomposition methods such as sequential minimal optimization algorithm and SVM^ are efficient iterative techniques for solving QP problems arising in SVMs. In each step, the decomposition method chooses a small number of variables and then solves the QP problem with respect to those selected variables. In this report, we propose a novel variable selection method based on conjugate gradient method and evaluate its effectiveness by using several benchmark data on both pattern classification and regression problems.
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Keyword(in English)	support vector machine / quadratic programming problem / decomposition method / working set selection / convergence
Paper #	NC2006-139
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Committee	NC
Conference Date	2007/3/7(1days)
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Paper Information
Registration To	Neurocomputing (NC)
Language	JPN
Title (in Japanese)	(See Japanese page)
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Title (in English)	On Variable Selection in Decomposition Methods for Support Vector Machines : Proposal and Experimental Evaluation of a Novel Variable Selection based on Conjugate Gradient Method
Sub Title (in English)
Keyword(1)	support vector machine
Keyword(2)	quadratic programming problem
Keyword(3)	decomposition method
Keyword(4)	working set selection
Keyword(5)	convergence
1st Author's Name	Yusuke KAWAZOE
1st Author's Affiliation	Graduate School of Information Science and Electrical Engineering, Kyushu University()
2nd Author's Name	Masashi KURANOSHITA
2nd Author's Affiliation	Graduate School of Information Science and Electrical Engineering, Kyushu University:(Present office)FUJIFILM Corporation
3rd Author's Name	Norikazu TAKAHASHI
3rd Author's Affiliation	Faculty of Information Science and Electrical Engineering, Kyushu University
4th Author's Name	Jun-ichi TAKEUCHI
4th Author's Affiliation	Faculty of Information Science and Electrical Engineering, Kyushu University
Date	2007-03-14
Paper #	NC2006-139
Volume (vol)	vol.106
Number (no)	588
Page	pp.pp.-
#Pages	6
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