A principled approach to network-based classification and data representation

Neurocomputing

Volumn 112, Issue , 2013, Pages 79-91

  Ruiz, Héctor ^a   Etchells, Terence A ^a   Jarman, Ian H ^a   Martín, José D ^b   Lisboa, Paulo J G ^a  

^a LIVERPOOL JOHN MOORES UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF VALENCIA   (Spain)

Author keywords

Community detection; Dataset visualisation; Fisher information; Interpretable model; Riemannian metric; Similarity network

Indexed keywords

BENCHMARK DATASETS; COMMUNITY DETECTION; CONDITIONAL DENSITY FUNCTION; DATA REPRESENTATIONS; FISHER INFORMATION; NEAREST-NEIGHBOUR CLASSIFIER; RIEMANNIAN METRICS; SIMILARITY NETWORK;

FISHER INFORMATION MATRIX; PATTERN RECOGNITION;

BENCHMARKING;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; CLUSTER ANALYSIS; CONCEPTUAL FRAMEWORK; DATA ANALYSIS; DATA MINING; FISHER INFORMATION; FISHER INFOTMATION METRIC; KERNEL METHOD; MATHEMATICAL ANALYSIS; MATHEMATICAL MODEL; MATHEMATICAL PARAMETERS; MEASUREMENT; NEWMAN ALGORITHM; PREDICTION; PRIORITY JOURNAL; PROBABILITY; PROCESS DEVELOPMENT;

EID: 84877603653     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2012.12.050     Document Type: Article

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