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Volumn , Issue , 2002, Pages 521-528

Knowledge-Based Support Vector Machine Classifiers

Author keywords

linear programming; support vector machines; use and refinement of prior knowledge

Indexed keywords

CLASSIFICATION (OF INFORMATION); DNA SEQUENCES; GENE ENCODING; KNOWLEDGE BASED SYSTEMS; LINEAR PROGRAMMING; VECTORS;

EID: 85156193010     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (69)

References (18)
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    • G. Fung, O. L. Mangasarian, and J. Shavlik. Knowledge-based support vector machine classifiers. Technical Report 01-09, Data Mining Institute, Computer Sciences Department, University of Wisconsin, Madison, Wisconsin, November 2001. ftp://ftp.cs.wisc.edu/pub/dmi/tech-reports/01-09.ps.
    • (2001) Knowledge-based support vector machine classifiers
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  • 8
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    • Technical Report 01-03, Data Mining Institute, Computer Sciences Department, University of Wisconsin, Madison, Wisconsin, March Computational Optimization and Applications, to appear
    • Y.-J. Lee, O. L. Mangasarian, and W. H. Wolberg. Survival-time classification of breast cancer patients. Technical Report 01-03, Data Mining Institute, Computer Sciences Department, University of Wisconsin, Madison, Wisconsin, March 2001. Computational Optimization and Applications, to appear. ftp://ftp.cs.wisc.edu/pub/dmi/tech-reports/Ol-03.ps.
    • (2001) Survival-time classification of breast cancer patients
    • Lee, Y.-J.1    Mangasarian, O. L.2    Wolberg, W. H.3
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    • Mangasarian, O. L.1
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    • Generalized support vector machines
    • A. Smola, P. Bartlett, B. Scholkopf, and D. Schuurmans, editors, pages Cambridge, MA, MIT Press
    • O. L. Mangasarian. Generalized support vector machines. In A. Smola, P. Bartlett, B. Scholkopf, and D. Schuurmans, editors, Advances in Large Margin Classifiers, pages 135-146, Cambridge, MA, 2000. MIT Press. ftp://ftp.cs.wisc.edu/math-prog/tech-reports/98-14.ps.
    • (2000) Advances in Large Margin Classifiers , pp. 135-146
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    • D. E. Rumelhart, G. E. Hinton, and R. J. Williams. Learning internal representations by error propagation. In D. E. Rumelhart and J. L. McClelland, editors, Parallel Distributed Processing, pages 318-362, Cambridge, Massachusetts, 1986. MIT Press.
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    • Prior knowledge in support vector kernels
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    • B. Scholkopf, P. Simard, A. Smola, and V. Vapnik. Prior knowledge in support vector kernels. In M. Jordan, M. Kearns, and S. Solla, editors, Advances in Neural Information Processing Systems 10, pages 640-646, Cambridge, MA, 1998. MIT Press.
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  • 16


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.