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Volumn 16, Issue 3, 2007, Pages 295-306

A data reduction approach for resolving the imbalanced data issue in functional genomics

Author keywords

Clustering; Data reduction; Imbalanced data; Neural network

Indexed keywords


EID: 34547507567     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-007-0089-7     Document Type: Article
Times cited : (40)

References (27)
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    • Mixture of expert agents for handling imbalanced data sets
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    • Kotsiantis SB, Pintelas PE (2003) Mixture of expert agents for handling imbalanced data sets. Ann Math Comput Teleinform 1(1):46-55
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    • Kotsiantis, S.B.1    Pintelas, P.E.2
  • 12
    • 11244278806 scopus 로고    scopus 로고
    • Asymmetric missing-data problems: Overcoming the lack of negative data in preference ranking
    • Kolcz A, Alspector J (2002) Asymmetric missing-data problems: overcoming the lack of negative data in preference ranking. Informat Retr 5(1):5-40
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    • Kolcz, A.1    Alspector, J.2
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    • A multiple resampling method for learning from imbalanced data sets
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    • Sampling approaches to learning from imbalanced datasets: Active learning, cost sensitive learning and beyond
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    • (2003) ICML-KDD'2003 Workshop: Learning from Imbalanced Data Sets
    • Abe, N.1
  • 23
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    • Robust classification for imprecise environments
    • Provost F, Fawcett T (2001) Robust classification for imprecise environments. Mach Learn 42/3:203-231
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    • Provost, F.1    Fawcett, T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.