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Bayesian Networks An Introduction

Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic;

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Bayesian Networks and Decision Graphs

This is a brand new edition of an essential work on Bayesian networks and decision graphs. It is an introduction to probabilistic graphical;

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Bayesian Artificial Intelligence

Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main;

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Bayesian Artificial Intelligence

Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main;

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Modeling and Reasoning with Bayesian Networks

This book is a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive;

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Modeling and Reasoning with Bayesian Networks

This book is a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive;

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Bayesian Networks

provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life;

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Probabilistic Graphical Models

This accessible text/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective;

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An Introduction to Bayesian Inference and Decision

An Introduction to Bayesian Inference and Decision is een boek van Robert L Winkler;

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An Introduction to Bayesian Inference in Econometrics

This is a classical reprint edition of the original 1971 edition of An Introduction to Bayesian Inference in Economics. This historical;

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Probabilistic Methods for Bioinformatics

explained in an accessible way using applications and case studies. The many useful applications of Bayesian networks that have been developed;

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Development of Clinical Decision Support Systems using Bayesian Networks

For the development of clinical decision support systems based on Bayesian networks, Mario A. Cypko investigates comprehensive expert;

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Bayesian Modeling Using WinBUGS

A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using WinBUGS provides an easily accessible;

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Bayesian Networks for Managing Learner Models in Adaptive Hypermedia Systems

learner models, and the behavior of an adaptive system varies depending on the data from the learner model and the learner's profile. Without;

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Bayesian Networks

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Probabilistic Graphical Models

This fully updated new edition of a uniquely accessible textbook/reference provides a general introduction to probabilistic graphical;

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Probabilistic Graphical Models

This fully updated new edition of a uniquely accessible textbook/reference provides a general introduction to probabilistic graphical;

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Bayesian Decision Analysis

data can be sampled and expert judgements elicited to support this analysis, and when and how an effective Bayesian decision analysis can be;

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Bayesian Inference for Gene Expression and Proteomics

data. Although there have been rapid developments in new technology and an inundation of statistical methods for addressing other types of high;

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Bayesian Inference For Gene Expression And Proteomics

data. Although there have been rapid developments in new technology and an inundation of statistical methods for addressing other types of high;

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Advanced Methodologies for Bayesian Networks

This volume constitutes the refereed proceedings of the Second International Workshop on Advanced Methodologies for Bayesian Networks;

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Bayesian Networks Handbook

A Bayesian network is also known as a Bayes network, belief network or causal probabilistic network. Bayesian belief networks are effective;

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Machine Learning

Machine Learning: A Bayesian and Optimization Perspective, 2nd edition, gives a unified perspective on machine learning by;

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The Bayesian Choice

This is an introduction to Bayesian statistics and decision theory, including advanced topics such as Monte Carlo methods. This new edition;

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An Introduction to Bayesian Inference, Methods and Computation

These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy;

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Principles Of Quantum Artificial Intelligence

This unique compendium presents an introduction to problem solving, information theory, statistical machine learning, stochastic methods;

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Data-Driven Computational Neuroscience

. This introduction for researchers and graduate students is the first in-depth, comprehensive treatment of statistical and machine learning;

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