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Volumn 6, Issue , 2007, Pages 3607-3612

Adaptive classifiers-ensemble system for tracking concept drift

Author keywords

Changing environments; Concept drift; Drift detection; Multiple classifiers system

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; DATA STRUCTURES; DATABASE SYSTEMS; ONLINE SYSTEMS; PROBLEM SOLVING; REAL TIME SYSTEMS;

EID: 38049021568     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLC.2007.4370772     Document Type: Conference Paper
Times cited : (44)

References (17)
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    • Dynamic weighted majority: A new ensemble method for tracking concept drift
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    • Kolter, J.Z.1    Maloof, M.A.2
  • 10
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    • Using additive expert ensembles to cope with concept drift
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  • 11
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    • Novelty detection: A review -part 1: Statistical approaches
    • M. Markou and S. Singh, "Novelty detection: a review -part 1: Statistical approaches," Signal Process., 83, 12, 2481-2497, 2003.
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    • Novelty detection: A review -part 2: Neural network based approaches
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  • 13
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    • J.R. Lewis and J. Sauro, When 100% really isn't 100%: Improving the accuracy of small-sample estimates of completion rates, J. Usability Studies, 1, 3, 136-150, 2006.
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    • Y. Freund and R.E. Schapire, A decision-theoretic generalization of on-line learning and an application to boosting, J. Comput. and Syst. Sci., 55, 1, 119-139, 1997.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.