Identifying critical variables of principal components for unsupervised feature selection

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 35, Issue 2, 2005, Pages 339-344

  Mao, K Z ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Backward elimination; Forward selection; Principal components analysis (PCA); Unsupervised feature selection

Indexed keywords

COMPUTATIONAL COMPLEXITY; COMPUTATIONAL METHODS; DATA REDUCTION; LEARNING ALGORITHMS; MATHEMATICAL TRANSFORMATIONS; PRINCIPAL COMPONENT ANALYSIS; SET THEORY;

BACKWARD ELIMINATION; DIMENSIONALITY REDUCTION; FEATURE ELIMINATION ALGORITHM; FEATURE EVALUATION; FORWARD SELECTION; UNSUPERVISED FEATURE SELECTION;

FEATURE EXTRACTION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; CLUSTER ANALYSIS; COMPUTER SIMULATION; EVALUATION; METHODOLOGY; PRINCIPAL COMPONENT ANALYSIS; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COMPUTER SIMULATION; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; PRINCIPAL COMPONENT ANALYSIS;

EID: 17444406668     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2004.843269     Document Type: Article

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