A fast approach for detection of erythemato-squamous diseases based on extreme learning machine with maximum relevance minimum redundancy feature selection

International Journal of Systems Science

Volumn 46, Issue 5, 2015, Pages 919-931

  Liu, Tong ^a   Hu, Liang ^a   Ma, Chao ^a   Wang, Zhi Yan ^a   Chen, Hui Ling ^a,b  

^a JILIN UNIVERSITY   (China)

^b WENZHOU UNIVERSITY   (China)

Author keywords

erythemato squamous diseases diagnosis; extreme learning machine; feature selection; medical diagnosis; MRMR

Indexed keywords

CLASSIFICATION (OF INFORMATION); DIAGNOSIS; DIMENSIONALITY REDUCTION; FEATURE EXTRACTION; KNOWLEDGE ACQUISITION; REDUNDANCY;

10-FOLD CROSS-VALIDATION; CLASSIFICATION ACCURACY; ERYTHEMATO-SQUAMOUS DISEASE; EXTREME LEARNING MACHINE; MACHINE-LEARNING DATABASE; MAXIMUM RELEVANCE MINIMUM REDUNDANCIES; MRMR; NUMBER OF HIDDEN NEURONS;

LEARNING SYSTEMS;

EID: 84918810095     PISSN: 00207721     EISSN: 14645319     Source Type: Journal    
DOI: 10.1080/00207721.2013.801096     Document Type: Article

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