Functional relevance learning in generalized learning vector quantization

Neurocomputing

Volumn 90, Issue , 2012, Pages 85-95

  Kästner, Marika ^a   Hammer, Barbara ^b   Biehl, Michael ^c   Villmann, Thomas ^a  

^a UNIVERSITY OF APPLIED SCIENCES MITTWEIDA   (Germany)

^b BIELEFELD UNIVERSITY   (Germany)

^c UNIVERSITY OF GRONINGEN   (Netherlands)

Author keywords

Feature weighting and selection; Functional vector quantization; Relevance learning; Sparse models

Indexed keywords

BASIS FUNCTIONS; CLASSIFICATION TASKS; FEATURE WEIGHTING; FUNCTIONAL APPROACH; FUNCTIONAL DATAS; FUNCTIONAL RELEVANCE; GENERALIZED LEARNING VECTOR QUANTIZATION; HIGH-DIMENSIONAL; LEARNING VECTOR QUANTIZATION; MODEL OPTIMIZATION; NUMBER OF DATUM; RELEVANCE LEARNING; RELEVANCE MODELS;

FEATURE EXTRACTION;

VECTOR QUANTIZATION;

ARTICLE; CLASSIFICATION ALGORITHM; DATA PROCESSING; LEARNING VECTOR QUANTIZATION; MACHINE LEARNING; PARAMETERS; PRIORITY JOURNAL; RELEVANCE LEARNING; STATISTICAL ANALYSIS; STATISTICAL MODEL;

EID: 84860237512     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2011.11.029     Document Type: Article

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