Probabilistic self-organizing maps for continuous data

IEEE Transactions on Neural Networks

Volumn 21, Issue 10, 2010, Pages 1543-1554

  López Rubio, Ezequiel ^a  

^a UNIVERSITY OF MÁLAGA   (Spain)

Author keywords

Classification; self organization; unsupervised learning; visualization

Indexed keywords

CLASSIFICATION; COMMONLY USED; COMPUTATIONAL INTELLIGENCE; CONTINUOUS DATA; CONTINUOUS PROBABILITY DISTRIBUTION; ESTIMATION THEORY; EXPECTATION MAXIMIZATION; INPUT SPACE; LEARNING SCHEMES; PROBABILISTIC APPROACHES; PROBABILISTIC METHODOLOGY; SELF-ORGANIZATION; SELF-ORGANIZATION MECHANISMS; SELF-ORGANIZING FEATURE MAP; STATE OF THE ART; STOCHASTIC APPROXIMATION METHODS; THEORETICAL FRAMEWORK; TYPICAL APPLICATION;

APPROXIMATION THEORY; ARTIFICIAL INTELLIGENCE; CONFORMAL MAPPING; IMAGE SEGMENTATION; SELF ORGANIZING MAPS; UNSUPERVISED LEARNING; VISUALIZATION;

PROBABILITY DISTRIBUTIONS;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; CLASSIFICATION; METHODOLOGY; PROBABILITY; STATISTICS; THEORETICAL MODEL;

ALGORITHMS; CLASSIFICATION; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); PROBABILITY; STOCHASTIC PROCESSES;

EID: 77957805746     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2010.2060208     Document Type: Article

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