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Volumn 5519 LNCS, Issue , 2009, Pages 82-91

A multiple expert approach to the class imbalance problem using inverse random under sampling

Author keywords

[No Author keywords available]

Indexed keywords

CLASS IMBALANCE PROBLEMS; DATA SETS; LEARNING METHODS; LINEAR DISCRIMINANTS; TRAINING SETS; UNDER-SAMPLING;

EID: 70349322730     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-02326-2_9     Document Type: Conference Paper
Times cited : (88)

References (14)
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    • A study of the bahavior of several methods for balancing machine learning training data
    • Batista, G., Prati, R.C., Monard, M.C.: A study of the bahavior of several methods for balancing machine learning training data. SIGKDD Explorations 6(20-29) (2004)
    • (2004) SIGKDD Explorations , vol.6 , Issue.20-29
    • Batista, G.1    Prati, R.C.2    Monard, M.C.3
  • 2
    • 70349349272 scopus 로고    scopus 로고
    • Blake, C, Keogh, E, Merz, C.J, UCI repository of machine learning databases
    • Blake, C., Keogh, E., Merz, C.J.: UCI repository of machine learning databases
  • 4
    • 70349349273 scopus 로고    scopus 로고
    • Chawla, N.V.: C4.5 and imbalanced data sets: Investigating the effect of sampling method, probabilistic estimate, and decision tree structure. In: Proceedings of the International Conference onMachine Learning (ICML 2003)Workshop on Learning from Imbalanced Data Sets II (2003)
    • Chawla, N.V.: C4.5 and imbalanced data sets: Investigating the effect of sampling method, probabilistic estimate, and decision tree structure. In: Proceedings of the International Conference onMachine Learning (ICML 2003)Workshop on Learning from Imbalanced Data Sets II (2003)
  • 6
    • 33750733902 scopus 로고    scopus 로고
    • An empirical analysis of under-sampling techniques to balance a protein structural class dataset
    • King, I, Wang, J, Chan, L.-W, Wang, D, eds, ICONIP 2006, Springer, Heidelberg
    • de Souto Marcilio, C.P., Bittencourt, V.G., Jose, A.F.C.: An empirical analysis of under-sampling techniques to balance a protein structural class dataset. In: King, I., Wang, J., Chan, L.-W., Wang, D. (eds.) ICONIP 2006. LNCS, vol. 4234, pp. 21-29. Springer, Heidelberg (2006)
    • (2006) LNCS , vol.4234 , pp. 21-29
    • de Souto Marcilio, C.P.1    Bittencourt, V.G.2    Jose, A.F.C.3
  • 8
    • 33845536164 scopus 로고    scopus 로고
    • The class imbalance problem: A systematic study
    • Japkowicz, M., Stephen, S.: The class imbalance problem: A systematic study. Intelligent data analysis (6), 429-449 (2002)
    • (2002) Intelligent data analysis , vol.6 , pp. 429-449
    • Japkowicz, M.1    Stephen, S.2
  • 11
    • 70349304538 scopus 로고    scopus 로고
    • Artificial Intelligence in Medicine
    • Improving Identification of Difficult Small Classes by Balancing Class Distribution, Springer, Heidelberg
    • Laurikkala, J.: Artificial Intelligence in Medicine. In: Improving Identification of Difficult Small Classes by Balancing Class Distribution. LNCS. Springer, Heidelberg (2001)
    • (2001) LNCS
    • Laurikkala, J.1


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