Feature weight estimation for gene selection: A local hyperlinear learning approach

BMC Bioinformatics

Volumn 15, Issue 1, 2014, Pages

  Cai, Hongmin ^a   Ruan, Peiying ^b   Ng, Michael ^c   Akutsu, Tatsuya ^b  

^a SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

^b KYOTO UNIVERSITY   (Japan)

^c HONG KONG BAPTIST UNIVERSITY   (Hong Kong)

Author keywords

Classification; Feature weighting; KNN; Local hyperplane; RELIEF

Indexed keywords

ALGORITHMS; BENCHMARKING; CLASSIFICATION (OF INFORMATION); EXPERIMENTS; GENE EXPRESSION; GEOMETRY; IMAGE RETRIEVAL; SUPPORT VECTOR MACHINES; CLUSTERING ALGORITHMS; DATA MINING; DISCRIMINANT ANALYSIS; GENES; LEARNING ALGORITHMS; MOTION COMPENSATION; NEAREST NEIGHBOR SEARCH;

CLASSIFICATION ALGORITHM; FEATURE SELECTION METHODS; FEATURE WEIGHTING; GENE EXPRESSION PROFILING; KNN; LINEAR DISCRIMINANT ANALYSIS; LOCAL HYPERPLANES; RELIEF; K NEAREST NEIGHBOR (KNN);

FEATURE EXTRACTION;

ALGORITHM; ARTICLE; BAYES THEOREM; BIOLOGY; CLUSTER ANALYSIS; DISCRIMINANT ANALYSIS; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENETIC DATABASE; GENETICS; HUMAN; METABOLISM; METHODOLOGY; NEOPLASM; SUPPORT VECTOR MACHINE;

ALGORITHMS; BAYES THEOREM; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; DISCRIMINANT ANALYSIS; GENE EXPRESSION PROFILING; HUMANS; NEOPLASMS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; SUPPORT VECTOR MACHINES;

EID: 84899071680     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-15-70     Document Type: Article

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