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Volumn 2431, Issue , 2002, Pages 62-73

The need for low bias algorithms in classification learning from large data sets

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION ERRORS; CLASSIFICATION LEARNING; COMPUTATION TIME; DATA SET SIZE; LARGE DATASETS; LOW BIAS; PARALLELISATION; SMALL DATA SET; STANDARD MACHINES; VARIANCE DECOMPOSITION;

EID: 84864854508     PISSN: 03029743     EISSN: 16113349     Source Type: Journal    
DOI: 10.1007/3-540-45681-3_6     Document Type: Article
Times cited : (45)

References (23)
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  • 15
    • 0004158427 scopus 로고    scopus 로고
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    • (1996) Arcing Classifiers
    • Breiman, L.1
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    • 2000
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    • On Bias, variance, 0/1-loss, and the curse-of-dimensionality
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    • (1997) Data Mining and Knowledge Discovery , vol.1 , pp. 55-77
    • Friedman, J.H.1
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    • An empirical comparison of voting classification algorithms: Bagging boosting and variants
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.