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Volumn , Issue , 2006, Pages 2529-2534

Improving feature subset selection using a genetic algorithm for microarray gene expression data

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION ACCURACY; DATA SETS; FEATURE SELECTION ALGORITHMS;

EID: 34547355032     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (36)

References (16)
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  • 2
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    • Gene selection for cancer classification using support vector machines
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  • 8
    • 27144489164 scopus 로고    scopus 로고
    • A tutorial on support vector machines for pattern recognition
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    • Burges, C.J.C.1
  • 9
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    • Y.L. Cun, J.S. Denker, S.A. Solla, Optimum brain damage, Advances in Neural Information Processing Systems II, D.S.Touretzky, Ed. Mateo, CA: Morgan Kaufmann Publishers, pp.598-605,1990
    • Y.L. Cun, J.S. Denker, S.A. Solla, Optimum brain damage, Advances in Neural Information Processing Systems II, D.S.Touretzky, Ed. Mateo, CA: Morgan Kaufmann Publishers, pp.598-605,1990
  • 10
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    • W. S. Noble, Support vector machine applications in computational biology, Kernel Methods in Computational Biology. B. Schoelkopf, KTsuda and J.-P. Vert, ed. MIT Press, 71-92, 2004
    • W. S. Noble, Support vector machine applications in computational biology, Kernel Methods in Computational Biology. B. Schoelkopf, KTsuda and J.-P. Vert, ed. MIT Press, 71-92, 2004
  • 12
    • 0033536012 scopus 로고    scopus 로고
    • Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays
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  • 13
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  • 14
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.