Bayes-N: An algorithm for learning Bayesian networks from data using local measures of information gain applied to classification problems

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2972, Issue , 2004, Pages 527-535

  Martínez Morales, Manuel ^a   Cruz Ramírez, Nicandro ^b   Jiménez Andrade, José Luis ^a   Garza Domínguez, Ramiro ^a  

^a UNIVERSIDAD VERACRUZANA   (Mexico)

^b LABORATORIO NACIONAL DE INFORMÁTICA AVANZADA   (Mexico)

Author keywords

Bayesian networks; Classification; Data mining; Machine learning; MDL

Indexed keywords

CLASSIFICATION (OF INFORMATION); DATA MINING; GRAPH THEORY; LEARNING ALGORITHMS; MATHEMATICAL MODELS; PROBABILITY DISTRIBUTIONS; PROBLEM SOLVING; ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLASSIFIERS; DIRECTED GRAPHS; LEARNING SYSTEMS;

BAYESIAN NETWORKS; DIRECTED ACYCLIC GRAPHS; INFORMATION GAIN; MDL; BAYESIAN NETWORK LEARNING; DIRECTED ACYCLIC GRAPH (DAG); EXPLANATORY VARIABLES; LEARNING BAYESIAN NETWORKS; MEASURES OF INFORMATION; NAIVE BAYES CLASSIFIERS; NEW CASE;

LEARNING SYSTEMS; BAYESIAN NETWORKS;

EID: 9444231147     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-24694-7_54     Document Type: Conference Paper

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