Locally linear embedding based on correntropy measure for visualization and classification

Neurocomputing

Volumn 80, Issue , 2012, Pages 19-30

  Daza Santacoloma, Genaro ^a   Castellanos Dominguez, German ^b   Principe, Jose C ^c  

^a CENTRO DE INVESTIGACIONES   (Colombia)

^b UNIVERSIDAD NACIONAL DE COLOMBIA   (Colombia)

^c UNIVERSITY OF FLORIDA   (United States)

Author keywords

Class label information; Classification; Correntropy; Locally linear embedding; Nonlinear dimensionality reduction; Visualization

Indexed keywords

CLASS LABELS; CLASSIFICATION ACCURACY; CORRENTROPY; DISCRIMINABILITY; EUCLIDEAN DISTANCE; HIGH-DIMENSIONAL FEATURE SPACE; INDUCED METRIC; INPUT DATAS; LINEAR DIMENSIONALITY REDUCTION; LOCALLY LINEAR EMBEDDING; LOW-DIMENSIONAL SPACES; NONLINEAR DIMENSIONALITY REDUCTION; NONLINEAR MANIFOLDS; NONLINEAR TECHNIQUES; REAL WORLD DATA;

CLASSIFICATION (OF INFORMATION); FACE RECOGNITION; FLOW VISUALIZATION; INPUT OUTPUT PROGRAMS; NONLINEAR ANALYSIS; STATISTICS; VIRTUAL REALITY; VISUALIZATION;

DATA VISUALIZATION;

ACCURACY; ARTICLE; CLASSIFICATION; CONTROLLED STUDY; INFORMATION PROCESSING; INTERMETHOD COMPARISON; LEARNING ALGORITHM; LINEAR DIMENSIONALITY REDUCTION; LOCALLY LINEAR EMBEDDING BASED ON CORRENTROPY MEASURE; MACHINE LEARNING; MATHEMATICAL ANALYSIS; NOISE; NONLINEAR DIMENSIONALITY REDUCTION; PATTERN RECOGNITION; PRIORITY JOURNAL;

EID: 84855229439     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2011.09.015     Document Type: Article

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