Principal component analysis using QR decomposition

International Journal of Machine Learning and Cybernetics

Volumn 4, Issue 6, 2013, Pages 679-683

  Sharma, Alok ^a,c   Paliwal, Kuldip K ^b   Imoto, Seiya ^a   Miyano, Satoru ^a  

^a UNIVERSITY OF TOKYO   (Japan)

^b GRIFFITH UNIVERSITY   (Australia)

^c UNIVERSITY OF THE SOUTH PACIFIC   (Fiji)

Author keywords

Computational complexity; Principal component analysis; QR decomposition; Singular value decomposition

Indexed keywords

DATA COVARIANCE MATRIX; FEATURE SPACE; MATLAB- SOFTWARE; NUMERICAL COMPARISON; PCA METHOD; Q R DECOMPOSITION; TRAINING FEATURES;

COMPUTATIONAL COMPLEXITY; COVARIANCE MATRIX; MATLAB; NUMERICAL METHODS; PRINCIPAL COMPONENT ANALYSIS; VECTOR SPACES;

SINGULAR VALUE DECOMPOSITION;

EID: 84885932018     PISSN: 18688071     EISSN: 1868808X     Source Type: Journal    
DOI: 10.1007/s13042-012-0131-7     Document Type: Article

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