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Volumn 20, Issue 6, 2009, Pages 1344-1350

Large scale classification with local diversity AdaBoost SVM algorithm

Author keywords

AdaBoost; Diversity; Ensemble learning; Large scale data; Local; Support vector machine

Indexed keywords

ADABOOST; DIVERSITY; ENSEMBLE LEARNING; LARGE SCALE DATA; LOCAL;

EID: 77957549546     PISSN: 10044132     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (12)

References (14)
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    • Liu, T.1    Yang, Y.2    Wan, H.3
  • 3
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    • Diversity measures for multiple classifier system analysis and design
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  • 8
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    • Selected tree classifier combination based on both accuracy and error diversity
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    • Shin, H.W.1    Sohn, S.Y.2
  • 9
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    • Bias-variance analysis of support vector machines for the development of SVM-based ensemble methods
    • Valentini G, Dietterich T G. Bias-variance analysis of support vector machines for the development of SVM-based ensemble methods. Journal of Machine Learning Research, 2004, 5: 725-775.
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  • 11
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    • Ensemble methods for classification of patients for personalized medicine with high-dimensional data
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    • Moon, H.1    Ahn, H.2    Kodell, R.L.3
  • 12
    • 10444259853 scopus 로고    scopus 로고
    • Creating diversity in ensembles using artificial data
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  • 13
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    • AdaBoost with SVMbased component classifiers
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  • 14
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    • A decision-theoretic generalization of on-line learning and an application to boosting
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    • Freund, Y.1    Schapire, R.E.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.