Learning naive Bayes models for multiple-instance learning with label proportions

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7023 LNAI, Issue , 2011, Pages 134-144

  Hernández González, Jerónimo ^a   Inza, Iñaki ^a  

^a UNIVERSITY OF THE BASQUE COUNTRY UPV EHU   (Spain)

Author keywords

EM algorithm; Multiple instance learning with label proportions; Naive Bayes; supervised classification

Indexed keywords

ARTIFICIAL INTELLIGENCE; BAYESIAN NETWORKS; CLASSIFICATION (OF INFORMATION); CLASSIFIERS; DEEP NEURAL NETWORKS; LEARNING SYSTEMS;

EM ALGORITHMS; MULTI-INSTANCE LEARNING; MULTIPLE INSTANCE LEARNING; NAIVE BAYES; NAIVE BAYES MODELS; REAL DATA SETS; STATE-OF-THE-ART APPROACH; SUPERVISED CLASSIFICATION;

LEARNING ALGORITHMS;

EID: 81055149948     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-25274-7_14     Document Type: Conference Paper

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