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Volumn 4224 LNCS, Issue , 2006, Pages 322-329

Pruning adaptive boosting ensembles by means of a genetic algorithm

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); ERROR CORRECTION; GENETIC ALGORITHMS; HEURISTIC METHODS; PROBLEM SOLVING;

EID: 33750542719     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11875581_39     Document Type: Conference Paper
Times cited : (15)

References (15)
  • 6
    • 0034250160 scopus 로고    scopus 로고
    • An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization
    • Dietterich, T.G.: An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization. Machine Learning 40(2) (2000) 139-157
    • (2000) Machine Learning , vol.40 , Issue.2 , pp. 139-157
    • Dietterich, T.G.1
  • 7
    • 0346786584 scopus 로고    scopus 로고
    • Arcing classifiers
    • Breiman, L.: Arcing classifiers. The Annals of Statistics 26(3) (1998) 801-849
    • (1998) The Annals of Statistics , vol.26 , Issue.3 , pp. 801-849
    • Breiman, L.1
  • 8
    • 0036567392 scopus 로고    scopus 로고
    • Ensembling neural networks: Many could be better than all
    • Zhou, Z.H., Wu, J., Tang, W.: Ensembling neural networks: Many could be better than all. Artificial Intelligence 137(1-2) (2002) 239-263
    • (2002) Artificial Intelligence , vol.137 , Issue.1-2 , pp. 239-263
    • Zhou, Z.H.1    Wu, J.2    Tang, W.3
  • 10
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman, L.: Bagging predictors. Machine Learning 24(2) (1996) 123-140
    • (1996) Machine Learning , vol.24 , Issue.2 , pp. 123-140
    • Breiman, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.