A cost-sensitive rotation forest algorithm for gene expression data classification

Neurocomputing

Volumn 228, Issue , 2017, Pages 270-276

  Lu, Huijuan ^a   Yang, Lei ^a   Yan, Ke ^a   Xue, Yu ^b   Gao, Zhigang ^c  

^a CHINA JILIANG UNIVERSITY   (China)

^b NANJING UNIVERSITY OF INFORMATION SCIENCE AND TECHNOLOGY   (China)

^c HANGZHOU DIANZI UNIVERSITY   (China)

Author keywords

Cost sensitive; Gene expression data; Misclassification cost; Rejection cost; Rotation forest; Test cost

Indexed keywords

CLASSIFICATION (OF INFORMATION); FORESTRY; GENE EXPRESSION; GENES; ROTATION;

COST-SENSITIVE; GENE EXPRESSION DATA; MISCLASSIFICATION COSTS; ROTATION FORESTS; TEST COST;

COSTS;

ARTICLE; CLASSIFIER; CONTROLLED STUDY; COST SENSITIVE ROTATION FOREST ALGORITHM; EXTREME LEARNING MACHINE; GENE EXPRESSION; INFORMATION PROCESSING; LEARNING ALGORITHM; MACHINE LEARNING; MEASUREMENT ACCURACY; PRINCIPAL COMPONENT ANALYSIS; RELIABILITY; SUPPORT VECTOR MACHINE;

EID: 85006321333     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2016.09.077     Document Type: Article

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