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Volumn 15, Issue , 2011, Pages 4266-4270

Classifiers selection for ensemble learning based on accuracy and diversity

Author keywords

Accuracy; Classifier selection; Diversity; Ensemble learning

Indexed keywords

ACCURACY; CLASSIFICATION PERFORMANCE; CLASSIFICATION TASKS; CLASSIFIER SELECTION; COMBINATION RULES; DATA SETS; DIVERSITY; DIVERSITY MEASURE; ENSEMBLE LEARNING; FINITE NUMBER; LEARNING METHODS; Q STATISTICS; SELECTION METHODS; UCI MACHINE LEARNING REPOSITORY;

EID: 84055219357     PISSN: 18777058     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1016/j.proeng.2011.08.800     Document Type: Conference Paper
Times cited : (65)

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    • Using diversity in classifier set selection for arabic handwritten recognition
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    • Nabiha Azizi, Nadir Farah, Mokhtar Sellami, and Abdel Ennaji. Using Diversity in Classifier Set Selection for Arabic Handwritten Recognition. N. El Gayar, J. Kittler, and F. Roli (Eds.): MCS 2010, LNCS 5997:235-244.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.