A multiobjective simultaneous learning framework for clustering and classification

IEEE Transactions on Neural Networks

Volumn 21, Issue 2, 2010, Pages 185-200

  Cai, Weiling ^a,b   Chen, Songcan ^a   Zhang, Daoqiang ^a  

^a NANJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS   (China)

^b NANJING NORMAL UNIVERSITY   (China)

Author keywords

Bayesian theory; Classification learning; Clustering learning; Multiobjective optimization; Pattern recognition

Indexed keywords

BAYESIAN THEORY; CLASS INFORMATION; CLASSIFICATION CRITERION; CLASSIFICATION LEARNING; CLASSIFICATION PERFORMANCE; CLUSTERING CENTERS; CLUSTERING CRITERIA; CLUSTERING LEARNING; CLUSTERING RESULTS; EMPIRICAL RESULTS; GENERALIZATION ABILITY; LEARNING FRAMEWORKS; LEARNING METHODS; MULTI OBJECTIVE; MULTIPLE OBJECTIVE FUNCTIONS; OPTIMALITY; PARETO-OPTIMALITY; SYNTHETIC AND REAL DATA;

BAYESIAN NETWORKS; CLUSTERING ALGORITHMS; MULTIOBJECTIVE OPTIMIZATION; PATTERN RECOGNITION;

LEARNING ALGORITHMS;

EID: 76749106573     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2009.2034741     Document Type: Article

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