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Volumn 3541, Issue , 2005, Pages 186-195

Using decision tree models and diversity measures in the selection of ensemble classification models

Author keywords

[No Author keywords available]

Indexed keywords

DECISION MAKING; DECISION THEORY; MARKETING; PROBLEM SOLVING;

EID: 26444610685     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/11494683_19     Document Type: Conference Paper
Times cited : (3)

References (16)
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    • An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization
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    • Dietterich, T.G.1
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    • Assessing the predictive accuracy of diversity measures with Domain-dependent, asymmetric misclassification costs
    • Gal-Or, M., May, J.H., Spangler, W.E., Assessing The Predictive Accuracy of Diversity Measures with Domain-Dependent, Asymmetric Misclassification Costs. Information Fusion, 6, 1, (2005), 37-48.
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    • Gal-Or, M.1    May, J.H.2    Spangler, W.E.3
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    • Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy
    • Kuncheva, L.I., Whitaker, C.J., Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Accuracy. Machine Learning, 51, 2, (2003), 181-207.
    • (2003) Machine Learning , vol.51 , Issue.2 , pp. 181-207
    • Kuncheva, L.I.1    Whitaker, C.J.2
  • 12
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    • Application of majority voting to pattern recognition: An analysis of its behavior and performance
    • Lam, L., Suen, C.Y., Application of Majority Voting to Pattern Recognition: An Analysis of Its Behavior and Performance. IEEE Transactions on Systems, Man and Cybernetics, 27, 5, (1997), 553-568.
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  • 15
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    • Relationships between combination methods and measures of diversity in combining classifiers
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.