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Volumn 42, Issue 7, 2009, Pages 1572-1581

A closed-form reduction of multi-class cost-sensitive learning to weighted multi-class learning

Author keywords

Classification; Cost sensitive learning; Statistical learning theory; Supervised learning

Indexed keywords

COST REDUCTION; STANDARDS; SUPERVISED LEARNING;

EID: 62349086709     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2008.12.011     Document Type: Article
Times cited : (19)

References (23)
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    • Ting, K.M.1
  • 10
    • 31344442851 scopus 로고    scopus 로고
    • Training cost-sensitive neural networks with methods addressing the class imbalance problem
    • Zhou Z.-H., and Liu X.-Y. Training cost-sensitive neural networks with methods addressing the class imbalance problem. IEEE Transactions on Knowledge and Data Engineering 18 1 (2006) 63-77
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    • Zhou, Z.-H.1    Liu, X.-Y.2
  • 12
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    • A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations
    • Chernoff H. A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations. Annals of Mathematical Statistics 23 (1952) 493-509
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    • Posterior probability support vector machines for unbalanced data
    • Tao Q., Wu G.-W., Wang F.-Y., and Wang J. Posterior probability support vector machines for unbalanced data. IEEE Transactions on Neural Networks 16 6 (2005) 1561-1573
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  • 23
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    • R Foundation for Statistical Computing, Vienna, Austria, ISBN3-900051-07-0
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    • (2007) R: A Language and Environment for Statistical Computing


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.