Probabilistic graphical models : principles and techniques / Daphne Koller , Nir Friedman

By: Koller, DaphneContributor(s): Friedman, NirMaterial type: TextTextLanguage: English Series: Adaptive computation and machine learningPublisher: Cambridge, MA : MIT Press, 2009Description: xxxv, 1233 páginas : ilustraciones ; 27 cmISBN: 9780262013192Title translated: Modelos gráficos probabilísticos : principios y técnicas / Daphne Koller , Nir FriedmanSubject(s): Modelado gráfico -- Estadísticas | Teoría de la decisión estadística bayesiana -- Métodos gráficos | EstadísticaDDC classification: 519.5
Contents:
Foundations -- Representation -- Undirected graphical models -- Local probabilistic models - Template-base-representations -- Gaussian network moel -- The exponential family -- Inference -- Exact inference. clique trees Onfernce as optimization -- Learning graphical models : oveview -- Parameter estimation -- Structure learning in Bayesian networks -- Actions and decisions -- Structure decisions problems
Abstract: Un marco general para construir y usar modelos probabilísticos de sistemas complejos que permitirían a una computadora usar la información disponible para tomar decisiones.
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Incluye referencias bibliográficas (páginas 1171-1207) e índice

Foundations -- Representation -- Undirected graphical models -- Local probabilistic models - Template-base-representations -- Gaussian network moel -- The exponential family -- Inference -- Exact inference. clique trees Onfernce as optimization -- Learning graphical models : oveview -- Parameter estimation -- Structure learning in Bayesian networks -- Actions and decisions -- Structure decisions problems

Un marco general para construir y usar modelos probabilísticos de sistemas complejos que permitirían a una computadora usar la información disponible para tomar decisiones.

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