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检索条件"主题词=learning from incomplete data"
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Structural-EM for learning PDG models from incomplete data
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INTERNATIONAL JOURNAL OF APPROXIMATE REASONING 2010年 第5期51卷 515-530页
作者: Nielsen, Jens D. Rumi, Rafael Salmeron, Antonio Univ Castilla La Mancha Dept Comp Sci Albacete 02071 Spain Univ Almeria Dept Appl Math & Stat Almeria 04120 Spain
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by other popular models, such as Bayesian ... 详细信息
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Structural-EM for learning PDG models from incomplete data
Structural-EM for learning PDG models from incomplete data
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4th European Workshop on Probabilistic Graphical Models
作者: Nielsen, Jens D. Rumi, Rafael Salmeron, Antonio Univ Castilla La Mancha Dept Comp Sci Albacete 02071 Spain Univ Almeria Dept Appl Math & Stat Almeria 04120 Spain
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by other popular models, such as Bayesian ... 详细信息
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learning Bayesian networks for clustering by means of constructive induction
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PATTERN RECOGNITION LETTERS 1999年 第11-13期20卷 1219-1230页
作者: Peña, JM Lozano, JA Larrañaga, P Univ Basque Country Dept Comp Sci & Artificial Intelligence Intelligent Syst Grp E-20080 San Sebastian Spain
The purpose of this paper is to present and evaluate a heuristic algorithm for learning Bayesian networks for clustering. Our approach is based upon improving the Naive-Bayes model by means of constructive induction. ... 详细信息
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