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Volumn 2009, Issue 562 CP, 2009, Pages 734-736

Feature selection based on bagging ensemble learning algorithm

Author keywords

Bagging; Ensemble Learning; Feature Count Measure; Feature Selection

Indexed keywords

BAGGING; CLASSIFICATION RULES; COUNT MEASURE; ENSEMBLE LEARNING; ENSEMBLE LEARNING ALGORITHM; FEATURE SELECTION; GENERALIZATION ABILITY; MACHINE-LEARNING;

EID: 78649896435     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1049/cp.2009.2058     Document Type: Conference Paper
Times cited : (3)

References (8)
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    • BAUER E, KOHAVI R. An empirical comparison of voting classification algorithms: bagging, boosting, and variants [J]. Machine Learning, 1999, 36(2):105-139.
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  • 3
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    • Yu, L.1    Liu, H.2
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    • Dietterich, T.1
  • 7
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  • 8
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    • Discretization in rough set theory [J]
    • Lijuan Hou, Guoyin Wang, Neng Nie, Yu Wu, 4Discretization in Rough Set Theory [J], Journal of computer science, 2000,27(12):89-94
    • (2000) Journal of computer science , vol.27 , Issue.12 , pp. 89-94
    • Hou, L.1    Wang, G.2    Nie, N.3    Yu, W.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.