Incorporating medical history to cost sensitive classification with lazy learning strategy

Qin, Z; Wang, T; Zhang, S

Incorporating medical history to cost sensitive classification with lazy learning strategy

Qin, Z Wang, T Zhang, S

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: Proceedings of the 2010 IEEE International Conference on Progress in Informatics and Computing, PIC 2010, 2010, pp. 19 - 23
Issue Date:: 2010-01

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Field	Value	Language
dc.contributor.author	Qin, Z	en_US
dc.contributor.author	Wang, T	en_US
dc.contributor.author	Zhang, S	en_US
dc.contributor.editor	NA	en_US
dc.date	2010-12-10	en_US
dc.date.issued	2010-01	en_US
dc.identifier.citation	Proceedings of the 2010 IEEE International Conference on Progress in Informatics and Computing, PIC 2010, 2010, pp. 19 - 23	en_US
dc.identifier.isbn	978-1-4244-6789-1	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16166
dc.description.abstract	This paper studies an actual and new setting of cost-sensitive learning, i.e., combining test data with medical history under multiple-scale cost constraints. With a new cost structure, an attribute selection strategy is incorporated to a lazy decision t	en_US
dc.publisher	IEEE	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP0985456
dc.relation.ispartof	Proceedings of the 2010 IEEE International Conference on Progress in Informatics and Computing, PIC 2010	en_US
dc.relation.ispartof	International Conference on Progress in Informatics and Computing	en_US
dc.relation.isbasedon	10.1109/PIC.2010.5687961	en_US
dc.rights	© 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.title	Incorporating medical history to cost sensitive classification with lazy learning strategy	en_US
dc.type	Conference Proceeding
utslib.location	United States	en_US
utslib.location.activity	Shanghai, China	en_US
utslib.for	1117 Public Health and Health Services	en_US
dc.location.activity	Shanghai, China	en_US
pubs.embargo.period	Not known	en_US
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.consider-herdc	true	en_US
pubs.place-of-publication	United States	en_US
pubs.start-date	2010-12-10	en_US

Abstract:

This paper studies an actual and new setting of cost-sensitive learning, i.e., combining test data with medical history under multiple-scale cost constraints. With a new cost structure, an attribute selection strategy is incorporated to a lazy decision t

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http://hdl.handle.net/10453/16166