Support Vector Machine For Outlier Detection In Breast Cancer Survivability Prediction

Thongkam, J; Xu, G; Zhang, Y; Huang, F

Support Vector Machine For Outlier Detection In Breast Cancer Survivability Prediction

Thongkam, J Xu, G Zhang, Y Huang, F

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Publisher:: Springer-verlag Berlin
Publication Type:: Conference
Citation:: Advanced Web And Network Technologies, And Applications, 2008, 4977 pp. 99 - 109
Issue Date:: 2008-01

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Field	Value	Language
dc.contributor.author	Thongkam, J
dc.contributor.author	Xu, G
dc.contributor.author	Zhang, Y
dc.contributor.author	Huang, F
dc.date.accessioned	2015-01-14T01:10:25Z
dc.date.issued	2008-01
dc.identifier.citation	Advanced Web And Network Technologies, And Applications, 2008, 4977 pp. 99 - 109
dc.identifier.issn	0302-9743
dc.identifier.uri	http://hdl.handle.net/10453/31515
dc.description.abstract	Finding, and removing misclassified instances are important steps ill data mining and machine learning that affect the performance of the data mining algorithm in general. In this paper, we propose a C-Support Vector Classification Filter (C-SVCF) to ide
dc.publisher	Springer-verlag Berlin
dc.relation.ispartof	10th Asia-Pacific Web Conference and Workshops
dc.relation.ispartof	Advanced Web And Network Technologies, And Applications
dc.subject	CLASSIFICATION PROBLEMS, ELIMINATION, Artificial Intelligence & Image Processing
dc.subject	CLASSIFICATION PROBLEMS
dc.subject	CLASSIFICATION PROBLEMS; ELIMINATION; Artificial Intelligence & Image Processing
dc.subject	ELIMINATION
dc.title	Support Vector Machine For Outlier Detection In Breast Cancer Survivability Prediction
dc.type	Conference
utslib.citation.volume	4977
utslib.location	Berlin
utslib.for	0801 Artificial Intelligence and Image Processing
dc.location.activity	Shenyang, PEOPLES R CHINA
pubs.embargo.period	Not known
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.declined	1970-01-01T00:00:00.0+1000

Abstract:

Finding, and removing misclassified instances are important steps ill data mining and machine learning that affect the performance of the data mining algorithm in general. In this paper, we propose a C-Support Vector Classification Filter (C-SVCF) to ide

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http://hdl.handle.net/10453/31515