Posterior probability support vector machines for unbalanced data

IEEE Transactions on Neural Networks

Volumn 16, Issue 6, 2005, Pages 1561-1573

  Tao, Qing ^a,b   Wu, Gao Wei ^a   Wang, Fei Yue ^a,c   Wang, Jue ^a  

^a INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^b Hefei New Star Institute of Applied Technology   (China)

^c UNIVERSITY OF ARIZONA   (United States)

Author keywords

SVM; Bayesian decision theory; Classification; Margin; Maximal margin algorithms; Posterior probability; Support vector machines (SVMs); Unbalanced data

Indexed keywords

DECISION THEORY; FUZZY SETS; LEARNING ALGORITHMS; OPTIMIZATION; PATTERN RECOGNITION; PROBABILITY DISTRIBUTIONS; STATISTICAL METHODS;

BAYESIAN DECISION THEORY; MAXIMAL MARGIN ALGORITHMS; POSTERIOR PROBABILITY SUPPORT VECTOR MACHINES (PPSVMS); UNBALANCED DATA;

LEARNING SYSTEMS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER SIMULATION; FACTUAL DATABASE; INFORMATION RETRIEVAL; METHODOLOGY; STATISTICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DATABASES, FACTUAL; INFORMATION STORAGE AND RETRIEVAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED;

EID: 28244467848     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2005.857955     Document Type: Article

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