Advanced Methodologies for Bayesian Networks

Download Advanced Methodologies for Bayesian Networks PDF Online Free

Author :
Publisher : Springer
ISBN 13 : 3319283790
Total Pages : 281 pages
Book Rating : 4.3/5 (192 download)

DOWNLOAD NOW!


Book Synopsis Advanced Methodologies for Bayesian Networks by : Joe Suzuki

Download or read book Advanced Methodologies for Bayesian Networks written by Joe Suzuki and published by Springer. This book was released on 2016-01-07 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the Second International Workshop on Advanced Methodologies for Bayesian Networks, AMBN 2015, held in Yokohama, Japan, in November 2015. The 18 revised full papers and 6 invited abstracts presented were carefully reviewed and selected from numerous submissions. In the International Workshop on Advanced Methodologies for Bayesian Networks (AMBN), the researchers explore methodologies for enhancing the effectiveness of graphical models including modeling, reasoning, model selection, logic-probability relations, and causality. The exploration of methodologies is complemented discussions of practical considerations for applying graphical models in real world settings, covering concerns like scalability, incremental learning, parallelization, and so on.

Advances in Bayesian Networks

Download Advances in Bayesian Networks PDF Online Free

Author :
Publisher : Springer
ISBN 13 : 3540398791
Total Pages : 334 pages
Book Rating : 4.5/5 (43 download)

DOWNLOAD NOW!


Book Synopsis Advances in Bayesian Networks by : José A. Gámez

Download or read book Advances in Bayesian Networks written by José A. Gámez and published by Springer. This book was released on 2013-06-29 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years probabilistic graphical models, especially Bayesian networks and decision graphs, have experienced significant theoretical development within areas such as artificial intelligence and statistics. This carefully edited monograph is a compendium of the most recent advances in the area of probabilistic graphical models such as decision graphs, learning from data and inference. It presents a survey of the state of the art of specific topics of recent interest of Bayesian Networks, including approximate propagation, abductive inferences, decision graphs, and applications of influence. In addition, Advances in Bayesian Networks presents a careful selection of applications of probabilistic graphical models to various fields such as speech recognition, meteorology or information retrieval.

Modeling and Reasoning with Bayesian Networks

Download Modeling and Reasoning with Bayesian Networks PDF Online Free

Author :
Publisher : Cambridge University Press
ISBN 13 : 0521884381
Total Pages : 561 pages
Book Rating : 4.5/5 (218 download)

DOWNLOAD NOW!


Book Synopsis Modeling and Reasoning with Bayesian Networks by : Adnan Darwiche

Download or read book Modeling and Reasoning with Bayesian Networks written by Adnan Darwiche and published by Cambridge University Press. This book was released on 2009-04-06 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis. It also treats exact and approximate inference algorithms at both theoretical and practical levels. The author assumes very little background on the covered subjects, supplying in-depth discussions for theoretically inclined readers and enough practical details to provide an algorithmic cookbook for the system developer.

Bayesian Networks and Decision Graphs

Download Bayesian Networks and Decision Graphs PDF Online Free

Author :
Publisher : Springer Science & Business Media
ISBN 13 : 0387682821
Total Pages : 457 pages
Book Rating : 4.3/5 (876 download)

DOWNLOAD NOW!


Book Synopsis Bayesian Networks and Decision Graphs by : Thomas Dyhre Nielsen

Download or read book Bayesian Networks and Decision Graphs written by Thomas Dyhre Nielsen and published by Springer Science & Business Media. This book was released on 2009-03-17 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a brand new edition of an essential work on Bayesian networks and decision graphs. It is an introduction to probabilistic graphical models including Bayesian networks and influence diagrams. The reader is guided through the two types of frameworks with examples and exercises, which also give instruction on how to build these models. Structured in two parts, the first section focuses on probabilistic graphical models, while the second part deals with decision graphs, and in addition to the frameworks described in the previous edition, it also introduces Markov decision process and partially ordered decision problems.

Bayesian Networks

Download Bayesian Networks PDF Online Free

Author :
Publisher :
ISBN 13 : 1839623225
Total Pages : 138 pages
Book Rating : 4.8/5 (396 download)

DOWNLOAD NOW!


Book Synopsis Bayesian Networks by : Douglas McNair

Download or read book Bayesian Networks written by Douglas McNair and published by . This book was released on 2019-11-06 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Learning Bayesian Networks

Download Learning Bayesian Networks PDF Online Free

Author :
Publisher : Prentice Hall
ISBN 13 :
Total Pages : 704 pages
Book Rating : 4.F/5 ( download)

DOWNLOAD NOW!


Book Synopsis Learning Bayesian Networks by : Richard E. Neapolitan

Download or read book Learning Bayesian Networks written by Richard E. Neapolitan and published by Prentice Hall. This book was released on 2004 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this first edition book, methods are discussed for doing inference in Bayesian networks and inference diagrams. Hundreds of examples and problems allow readers to grasp the information. Some of the topics discussed include Pearl's message passing algorithm, Parameter Learning: 2 Alternatives, Parameter Learning r Alternatives, Bayesian Structure Learning, and Constraint-Based Learning. For expert systems developers and decision theorists.

Bayesian Networks

Download Bayesian Networks PDF Online Free

Author :
Publisher : John Wiley & Sons
ISBN 13 : 9780470994542
Total Pages : 446 pages
Book Rating : 4.9/5 (945 download)

DOWNLOAD NOW!


Book Synopsis Bayesian Networks by : Olivier Pourret

Download or read book Bayesian Networks written by Olivier Pourret and published by John Wiley & Sons. This book was released on 2008-04-30 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields.

Modeling and Reasoning with Bayesian Networks

Download Modeling and Reasoning with Bayesian Networks PDF Online Free

Author :
Publisher : Cambridge University Press
ISBN 13 : 1139478907
Total Pages : 549 pages
Book Rating : 4.1/5 (394 download)

DOWNLOAD NOW!


Book Synopsis Modeling and Reasoning with Bayesian Networks by : Adnan Darwiche

Download or read book Modeling and Reasoning with Bayesian Networks written by Adnan Darwiche and published by Cambridge University Press. This book was released on 2009-04-06 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis. It also treats exact and approximate inference algorithms at both theoretical and practical levels. The treatment of exact algorithms covers the main inference paradigms based on elimination and conditioning and includes advanced methods for compiling Bayesian networks, time-space tradeoffs, and exploiting local structure of massively connected networks. The treatment of approximate algorithms covers the main inference paradigms based on sampling and optimization and includes influential algorithms such as importance sampling, MCMC, and belief propagation. The author assumes very little background on the covered subjects, supplying in-depth discussions for theoretically inclined readers and enough practical details to provide an algorithmic cookbook for the system developer.

Advances in Supervised and Unsupervised Learning of Bayesian Networks

Download Advances in Supervised and Unsupervised Learning of Bayesian Networks PDF Online Free

Author :
Publisher : LAP Lambert Academic Publishing
ISBN 13 : 9783838333441
Total Pages : 224 pages
Book Rating : 4.3/5 (334 download)

DOWNLOAD NOW!


Book Synopsis Advances in Supervised and Unsupervised Learning of Bayesian Networks by : Guzmán Santafé

Download or read book Advances in Supervised and Unsupervised Learning of Bayesian Networks written by Guzmán Santafé and published by LAP Lambert Academic Publishing. This book was released on 2010-08 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supervised classification and data clustering are two fundamental disciplines of data mining and machine learning where probabilistic graphical models, and particularly Bayesian networks, have become very popular paradigms. This book aims to contribute to the state of the art of both supervised classification and data clustering disciplines by providing new algorithms to learn Bayesian networks. On the one hand, the contributions related to supervised classification are focused on the discriminative learning of Bayesian network classifiers. Part of this book tries to motivate the use of this discriminative approach and presents new proposals to learn both structure and parameters of Bayesian network classifiers from a discriminative point of view. On the other hand, the part related to data clustering introduces new methods to deal with Bayesian model averaging for clustering. Additionally, the proposed methods are evaluated in diferent sinthetic and real datasets including a real problem taken from the field of population genetics.

Bayesian Networks

Download Bayesian Networks PDF Online Free

Author :
Publisher : Wiley
ISBN 13 : 0470684038
Total Pages : 366 pages
Book Rating : 4.4/5 (76 download)

DOWNLOAD NOW!


Book Synopsis Bayesian Networks by : Timo Koski

Download or read book Bayesian Networks written by Timo Koski and published by Wiley. This book was released on 2009-09-24 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout. Features include: An introduction to Dirichlet Distribution, Exponential Families and their applications. A detailed description of learning algorithms and Conditional Gaussian Distributions using Junction Tree methods. A discussion of Pearl's intervention calculus, with an introduction to the notion of see and do conditioning. All concepts are clearly defined and illustrated with examples and exercises. Solutions are provided online. This book will prove a valuable resource for postgraduate students of statistics, computer engineering, mathematics, data mining, artificial intelligence, and biology. Researchers and users of comparable modelling or statistical techniques such as neural networks will also find this book of interest.

Innovations in Bayesian Networks

Download Innovations in Bayesian Networks PDF Online Free

Author :
Publisher : Springer Science & Business Media
ISBN 13 : 3540850651
Total Pages : 324 pages
Book Rating : 4.5/5 (48 download)

DOWNLOAD NOW!


Book Synopsis Innovations in Bayesian Networks by : Dawn E. Holmes

Download or read book Innovations in Bayesian Networks written by Dawn E. Holmes and published by Springer Science & Business Media. This book was released on 2008-10-02 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian networks currently provide one of the most rapidly growing areas of research in computer science and statistics. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. Each of the twelve chapters is self-contained. Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Graduate students since it shows the direction of current research.

Bayesian Networks in Educational Assessment

Download Bayesian Networks in Educational Assessment PDF Online Free

Author :
Publisher : Springer
ISBN 13 : 1493921258
Total Pages : 678 pages
Book Rating : 4.4/5 (939 download)

DOWNLOAD NOW!


Book Synopsis Bayesian Networks in Educational Assessment by : Russell G. Almond

Download or read book Bayesian Networks in Educational Assessment written by Russell G. Almond and published by Springer. This book was released on 2015-03-10 with total page 678 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences. This innovative volume is the first comprehensive treatment exploring how they can be applied to design and analyze innovative educational assessments. Part I develops Bayes nets’ foundations in assessment, statistics, and graph theory, and works through the real-time updating algorithm. Part II addresses parametric forms for use with assessment, model-checking techniques, and estimation with the EM algorithm and Markov chain Monte Carlo (MCMC). A unique feature is the volume’s grounding in Evidence-Centered Design (ECD) framework for assessment design. This “design forward” approach enables designers to take full advantage of Bayes nets’ modularity and ability to model complex evidentiary relationships that arise from performance in interactive, technology-rich assessments such as simulations. Part III describes ECD, situates Bayes nets as an integral component of a principled design process, and illustrates the ideas with an in-depth look at the BioMass project: An interactive, standards-based, web-delivered demonstration assessment of science inquiry in genetics. This book is both a resource for professionals interested in assessment and advanced students. Its clear exposition, worked-through numerical examples, and demonstrations from real and didactic applications provide invaluable illustrations of how to use Bayes nets in educational assessment. Exercises follow each chapter, and the online companion site provides a glossary, data sets and problem setups, and links to computational resources.

Bayesian Networks

Download Bayesian Networks PDF Online Free

Author :
Publisher : CRC Press
ISBN 13 : 1000410382
Total Pages : 275 pages
Book Rating : 4.0/5 (4 download)

DOWNLOAD NOW!


Book Synopsis Bayesian Networks by : Marco Scutari

Download or read book Bayesian Networks written by Marco Scutari and published by CRC Press. This book was released on 2021-07-28 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains the material step-by-step starting from meaningful examples Steps detailed with R code in the spirit of reproducible research Real world data analyses from a Science paper reproduced and explained in detail Examples span a variety of fields across social and life sciences Overview of available software in and outside R

Advances in Probabilistic Graphical Models

Download Advances in Probabilistic Graphical Models PDF Online Free

Author :
Publisher : Springer
ISBN 13 : 3540689966
Total Pages : 386 pages
Book Rating : 4.5/5 (46 download)

DOWNLOAD NOW!


Book Synopsis Advances in Probabilistic Graphical Models by : Peter Lucas

Download or read book Advances in Probabilistic Graphical Models written by Peter Lucas and published by Springer. This book was released on 2007-06-12 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together important topics of current research in probabilistic graphical modeling, learning from data and probabilistic inference. Coverage includes such topics as the characterization of conditional independence, the learning of graphical models with latent variables, and extensions to the influence diagram formalism as well as important application fields, such as the control of vehicles, bioinformatics and medicine.

Introduction to Bayesian Networks

Download Introduction to Bayesian Networks PDF Online Free

Author :
Publisher : Springer
ISBN 13 : 9780387915029
Total Pages : 178 pages
Book Rating : 4.9/5 (15 download)

DOWNLOAD NOW!


Book Synopsis Introduction to Bayesian Networks by : Finn V. Jensen

Download or read book Introduction to Bayesian Networks written by Finn V. Jensen and published by Springer. This book was released on 1997-08-15 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Disk contains: Tool for building Bayesian networks -- Library of examples -- Library of proposed solutions to some exercises.

Bayesian Network Technologies: Applications and Graphical Models

Download Bayesian Network Technologies: Applications and Graphical Models PDF Online Free

Author :
Publisher : IGI Global
ISBN 13 : 159904143X
Total Pages : 368 pages
Book Rating : 4.5/5 (99 download)

DOWNLOAD NOW!


Book Synopsis Bayesian Network Technologies: Applications and Graphical Models by : Mittal, Ankush

Download or read book Bayesian Network Technologies: Applications and Graphical Models written by Mittal, Ankush and published by IGI Global. This book was released on 2007-03-31 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides an excellent, well-balanced collection of areas where Bayesian networks have been successfully applied; it describes the underlying concepts of Bayesian Networks with the help of diverse applications, and theories that prove Bayesian networks valid"--Provided by publisher.

Special Feature Advanced Methodologies for Bayesian Networks

Download Special Feature Advanced Methodologies for Bayesian Networks PDF Online Free

Author :
Publisher :
ISBN 13 :
Total Pages : 94 pages
Book Rating : 4.:/5 (17 download)

DOWNLOAD NOW!


Book Synopsis Special Feature Advanced Methodologies for Bayesian Networks by : Maomi Ueno

Download or read book Special Feature Advanced Methodologies for Bayesian Networks written by Maomi Ueno and published by . This book was released on 2012 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: