A framework for probabilistic combination of multiple classifiers at an abstract level

Engineering Applications of Artificial Intelligence

Volumn 10, Issue 4, 1997, Pages 379-385

  Kang, Hee Joong ^a,b   Kim, Kawon ^a   Kim, Jin H ^a  

^a Korea Advanced Institute of Science and Technology (KAIST)   (South Korea)

^b SAMSUNG Electronics   (South Korea)

Author keywords

Bayesian formalism; Combining multiple classifiers; High order probability distributions; Kth order dependency; Probabilistic combination; Product approximation

Indexed keywords

APPROXIMATION THEORY; DATABASE SYSTEMS; DECISION THEORY; PERFORMANCE; PROBABILITY;

BAYESIAN FORMALISM; PROBABILISTIC COMBINATION; PRODUCT APPROXIMATION;

PATTERN RECOGNITION;

EID: 0031198818     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/s0952-1976(97)00020-1     Document Type: Article

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