Data visualization and dimensionality reduction using kernel maps with a reference point

IEEE Transactions on Neural Networks

Volumn 19, Issue 9, 2008, Pages 1501-1517

  Suykens, Johan A K ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

Constrained optimization; Data visualization; Dimensionality reduction; Feature map; Kernel methods; Least squares support vector machines (LS SVMs); Positive definite kernel; Validation

Indexed keywords

CANNING; CURVE FITTING; DATA FUSION; EIGENVALUES AND EIGENFUNCTIONS; LEARNING SYSTEMS; LEAST SQUARES APPROXIMATIONS; LINEAR SYSTEMS; MAPS; OPTICAL PROJECTORS; SENSOR DATA FUSION; SUPPORT VECTOR MACHINES; TWO PHASE FLOW; VISUALIZATION;

CONSTRAINED OPTIMIZATION; DIMENSIONALITY REDUCTION; DUAL MODEL; EIGEN VALUE PROBLEMS; FEATURE MAP; KERNEL METHODS; LEAST SQUARES SUPPORT VECTOR MACHINES (LS-SVMS); LEAST-SQUARES SUPPORT VECTOR MACHINE; LOW-DIMENSIONAL SPACE; MUTUAL DISTANCES; POSITIVE-DEFINITE KERNEL; PROBLEM FORMULATION; REAL-LIFE DATA SETS; REFERENCE POINT; VALIDATION;

DATA VISUALIZATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER GRAPHICS; COMPUTER INTERFACE; COMPUTER SIMULATION; DATA BASE; FACTUAL DATABASE; INFORMATION PROCESSING; METHODOLOGY; THEORETICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER GRAPHICS; COMPUTER SIMULATION; DATA COMPRESSION; DATABASE MANAGEMENT SYSTEMS; DATABASES, FACTUAL; MODELS, THEORETICAL; PATTERN RECOGNITION, AUTOMATED; USER-COMPUTER INTERFACE;

EID: 52149103339     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2008.2000807     Document Type: Article

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