Probabilistic Graphical Models: Principles and Applications by Luis Enrique Sucar

By Luis Enrique Sucar

This obtainable text/reference offers a normal advent to probabilistic graphical types (PGMs) from an engineering point of view. The ebook covers the basics for every of the most sessions of PGMs, together with illustration, inference and studying rules, and experiences real-world functions for every form of version. those purposes are drawn from a huge variety of disciplines, highlighting the various makes use of of Bayesian classifiers, hidden Markov types, Bayesian networks, dynamic and temporal Bayesian networks, Markov random fields, impact diagrams, and Markov determination approaches. positive factors: offers a unified framework encompassing all the major periods of PGMs; describes the sensible software of different recommendations; examines the most recent advancements within the box, protecting multidimensional Bayesian classifiers, relational graphical versions and causal types; offers routines, feedback for additional interpreting, and ideas for examine or programming initiatives on the finish of every chapter.

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