Laplacian linear discriminant analysis approach to unsupervised feature selection

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 6, Issue 4, 2009, Pages 605-614

  Niijima, Satoshi ^a   Okuno, Yasushi ^a  

^a KYOTO UNIVERSITY   (Japan)

Author keywords

Graph Laplacian; Linear discriminant analysis; Microarray data analysis; Unsupervised feature selection

Indexed keywords

BIO-MARKER DISCOVERY; DATA SETS; EXPLORATORY DATA ANALYSIS; FEATURE SELECTION; FILTER METHOD; FISHER SCORE; GENOMICS; GRAPH LAPLACIAN; HIGH DIMENSIONALITY; LAPLACIANS; LINEAR DISCRIMINANT ANALYSIS; MASS SPECTROMETRY DATA; MICROARRAY DATA; MICROARRAY DATA ANALYSIS; NOVEL ALGORITHM; PROTEOMICS; PUBLIC DATA; RECURSIVE FEATURE ELIMINATION; SMALL SAMPLE SIZE; TWO-STATE; UNSUPERVISED FEATURE SELECTION; UNSUPERVISED METHOD;

ALGORITHMS; COMPUTATION THEORY; DISCRIMINANT ANALYSIS; FACE RECOGNITION; FEATURE EXTRACTION; IMAGE RETRIEVAL; LAPLACE TRANSFORMS; MASS SPECTROMETRY; MICROARRAYS; MOLECULAR BIOLOGY; SINGULAR VALUE DECOMPOSITION;

DATA HANDLING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGY; COMPUTER LANGUAGE; COMPUTER PROGRAM; DISCRIMINANT ANALYSIS; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; HUMAN; METHODOLOGY; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL BIOLOGY; DISCRIMINANT ANALYSIS; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, NEOPLASTIC; HUMANS; MODELS, STATISTICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PATTERN RECOGNITION, AUTOMATED; PROGRAMMING LANGUAGES; SOFTWARE;

EID: 75449099314     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2007.70257     Document Type: Article

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