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Volumn , Issue , 2009, Pages

An experimental comparison of MES aggregation rules in case of imbalanced datasets

Author keywords

[No Author keywords available]

Indexed keywords

BALANCED CLASSIFIERS; COMBINATION RULES; DATA SETS; EXPERIMENTAL COMPARISON; IMBALANCED DATASET; PREDICTIVE ACCURACY; RANDOM SELECTION; SELECTION FRAMEWORK; TRAINING SETS;

EID: 70449652352     PISSN: 10637125     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CBMS.2009.5255382     Document Type: Conference Paper
Times cited : (10)

References (19)
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    • (2004) ACM SIGKDD Explorations Newsletter , vol.6 , Issue.1 , pp. 20-29
    • Batista, G.E.1    Prati, R.C.2    Monard, M.C.3
  • 8
    • 37249032372 scopus 로고    scopus 로고
    • chapter On Rejecting Unreliably Classified Patterns Springer- VerlagHeidelberg
    • P. Foggia, G. Percannella, C. Šansone, and M. Vento. Multiple Classifier Systems, volume 4472, chapter On Rejecting Unreliably Classified Patterns, pages 282-291. Springer-Verlag Heidelberg, 2007.
    • (2007) Multiple Classifier Systems , vol.4472 , pp. 282-291
    • Foggia, P.1    Percannella, G.2    Šansone, C.3    Vento, M.4
  • 9
    • 84958754386 scopus 로고    scopus 로고
    • Support Vector Machines with Embedded Reject Option
    • G. Fumera and F. Roli. Support Vector Machines with Embedded Reject Option. Lecture Notes in Computer Science, pages 68-82, 2002.
    • (2002) Lecture Notes in Computer Science , pp. 68-82
    • Fumera, G.1    Roli, F.2
  • 13
    • 0001972236 scopus 로고    scopus 로고
    • Addressing the curse of imbalanced training sets: One-sided selection
    • Morgan Kaufmann Publishers, Inc.
    • M. Kubat and S. Matwin. Addressing the curse of imbalanced training sets: One-sided selection. In Machine Learning-International Workshop Then Conference, pages 179-186. Morgan Kaufmann Publishers, Inc., 1997.
    • (1997) Machine Learning-International Workshop Then Conference, Pages , pp. 179-186
    • Kubat, M.1    Matwin, S.2
  • 14
    • 0033645509 scopus 로고    scopus 로고
    • Clustering-and-selection model for classifier combination
    • Knowledge-Based Intelligent Engineering Systems and Allied Technologies, 2000.
    • L. I. Kuncheva. Clustering-and-selection model for classifier combination. In Knowledge-Based Intelligent Engineering Systems and Allied Technologies, 2000. Proceedings. Fourth International Conference on, volume 1, 2000.
    • (2000) Proceedings. Fourth International Conference on , vol.1
    • Kuncheva, L.I.1
  • 15
    • 0034830461 scopus 로고    scopus 로고
    • Decision templates for multiple classifier fusion: An experimental comparison
    • DOI 10.1016/S0031-3203(99)00223-X
    • [15] L. I. Kuncheva, J. C. Bezděk, and R. P. W. Duin. Decision templates for multiple classifier fusion: an experimental comparison. Pattern Recognition, 34:299-314, 2001. (Pubitemid 32871876)
    • (2001) Pattern Recognition , vol.34 , Issue.2 , pp. 299-314
    • Kuncheva, L.I.1    Bezdek, J.C.2    Duin, R.P.W.3
  • 18
    • 1442275185 scopus 로고    scopus 로고
    • Learning when training data are costly: The effect of class distribution on tree induction
    • G. M. Weiss and F. Provost. Learning when training data are costly: the effect of class distribution on tree induction. Journal of Artificial Intelligence Research, 19:315-354, 2003.
    • (2003) Journal of Artificial Intelligence Research , vol.19 , pp. 315-354
    • Weiss, G.M.1    Provost, F.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.