Local and global preserving semisupervised dimensionality reduction based on random subspace for cancer classification

IEEE Journal of Biomedical and Health Informatics

Volumn 18, Issue 2, 2014, Pages 500-507

  Cai, Xianfa ^a,b   Wei, Jia ^b   Wen, Guihua ^b   Yu, Zhiwen ^b  

^a GUANGDONG PHARMACEUTICAL UNIVERSITY   (China)

^b SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Cancer classification; dimensionality reduction; graph construction; random subspace; semisupervised learning

Indexed keywords

CLUSTERING ALGORITHMS; COMPUTER AIDED DIAGNOSIS; DATA REDUCTION; DISEASES; GENE EXPRESSION; GRAPH ALGORITHMS; MIXTURES; PROBABILITY DISTRIBUTIONS; SEMI-SUPERVISED LEARNING;

CANCER CLASSIFICATION; GENE EXPRESSION DATASETS; GEOMETRIC DISTRIBUTION; GRAPH CONSTRUCTION; HIGH DIMENSIONAL DATA; HIGH-DIMENSIONAL; LOCAL AND GLOBAL PRESERVING; RANDOM SUBSPACES;

DIMENSIONALITY REDUCTION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CLASSIFICATION; DNA MICROARRAY; GENE EXPRESSION PROFILING; GENETICS; HUMAN; METABOLISM; METHODOLOGY; NEOPLASM;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; GENE EXPRESSION PROFILING; HUMANS; NEOPLASMS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PATTERN RECOGNITION, AUTOMATED;

EID: 84896445930     PISSN: 21682194     EISSN: None     Source Type: Journal    
DOI: 10.1109/JBHI.2013.2281985     Document Type: Article

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