Advanced Methodologies For Bayesian Networks

Author : Joe Suzuki,Maomi Ueno
Publisher : Springer
Page : 281 pages
File Size : 48,9 Mb
Release : 2016-01-07
Category : Computers
ISBN : 9783319283791

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Advanced Methodologies for Bayesian Networks by Joe Suzuki,Maomi Ueno Pdf

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.

Author : Adnan Darwiche
Publisher : Cambridge University Press
Page : 561 pages
File Size : 40,9 Mb
Release : 2009-04-06
Category : Computers
ISBN : 9780521884389

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Modeling and Reasoning with Bayesian Networks by Adnan Darwiche Pdf

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.

Author : Adnan Darwiche
Publisher : Cambridge University Press
Page : 549 pages
File Size : 43,5 Mb
Release : 2009-04-06
Category : Computers
ISBN : 9781139478908

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Modeling and Reasoning with Bayesian Networks by Adnan Darwiche Pdf

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.

Author : Richard E. Neapolitan
Publisher : Prentice Hall
Page : 704 pages
File Size : 50,7 Mb
Release : 2004
Category : Computers
ISBN : STANFORD:36105111872318

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Learning Bayesian Networks by Richard E. Neapolitan Pdf

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.

Author : Khosrow-Pour, D.B.A., Mehdi
Publisher : IGI Global
Page : 1221 pages
File Size : 43,5 Mb
Release : 2018-09-28
Category : Computers
ISBN : 9781522573692

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Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction by Khosrow-Pour, D.B.A., Mehdi Pdf

As modern technologies continue to develop and evolve, the ability of users to adapt with new systems becomes a paramount concern. Research into new ways for humans to make use of advanced computers and other such technologies through artificial intelligence and computer simulation is necessary to fully realize the potential of tools in the 21st century. Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction provides emerging research in advanced trends in robotics, AI, simulation, and human-computer interaction. Readers will learn about the positive applications of artificial intelligence and human-computer interaction in various disciples such as business and medicine. This book is a valuable resource for IT professionals, researchers, computer scientists, and researchers invested in assistive technologies, artificial intelligence, robotics, and computer simulation.

Author : Douglas McNair
Publisher : Unknown
Page : 138 pages
File Size : 52,7 Mb
Release : 2019-11-06
Category : Electronic
ISBN : 9781839623226

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Bayesian Networks by Douglas McNair Pdf

Author : Ionut B. Brandusoiu
Publisher : GAER Publishing House
Page : 76 pages
File Size : 40,6 Mb
Release : 2020-08-19
Category : Computers
ISBN : 9789737208071

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HOW TO FINE-TUNE BAYESIAN NETWORKS FOR CLASSIFICATION by Ionut B. Brandusoiu Pdf

This book covers in the first part the theoretical aspects of Bayesian networks and their functionality, and then based on the discussed concepts it explains how to find-tune a Bayesian network to yield highly accurate prediction results which are adaptable to any classification tasks. The introductory part is extremely beneficial to someone new to learning Bayesian networks, while the more advanced notions are useful for everyone who wants to understand the mathematics behind Bayesian networks and how to find-tune them in order to generate the best predictive performance of a certain classification model.

Author : Khosrow-Pour, D.B.A., Mehdi
Publisher : IGI Global
Page : 1482 pages
File Size : 55,9 Mb
Release : 2018-09-14
Category : Business & Economics
ISBN : 9781522573630

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Advanced Methodologies and Technologies in Business Operations and Management by Khosrow-Pour, D.B.A., Mehdi Pdf

Businesses consistently work on new projects, products, and workflows to remain competitive and successful in the modern business environment. To remain zealous, businesses must employ the most effective methods and tools in human resources, project management, and overall business plan execution as competitors work to succeed as well. Advanced Methodologies and Technologies in Business Operations and Management provides emerging research on business tools such as employee engagement, payout policies, and financial investing to promote operational success. While highlighting the challenges facing modern organizations, readers will learn how corporate social responsibility and utilizing artificial intelligence improve a company’s culture and management. This book is an ideal resource for executives and managers, researchers, accountants, and financial investors seeking current research on business operations and management.

Author : Takashi Onoda,Daisuke Bekki,Eric Mc Cready
Publisher : Springer Science & Business Media
Page : 351 pages
File Size : 51,8 Mb
Release : 2012-01-10
Category : Computers
ISBN : 9783642256547

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New Frontiers in Artificial Intelligence by Takashi Onoda,Daisuke Bekki,Eric Mc Cready Pdf

This book constitutes the thoroughly refereed post-proceedings of four workshops held as satellite events of the JSAI International Symposia on Artificial Intelligence 2010, in Tokyo, Japan, in November 2010. The 28 revised full papers with four papers for the following four workshops presented were carefully reviewed and selected from 70 papers. The papers are organized in sections Logic and Engineering of Natural Language Semantics (LENLS), Juris-Informatics (JURISIN), Advanced Methodologies for Bayesian Networks (AMBN), and Innovating Service Systems (ISS).

Author : Olivier Pourret,Patrick Naïm,Bruce Marcot
Publisher : John Wiley & Sons
Page : 446 pages
File Size : 52,7 Mb
Release : 2008-04-30
Category : Mathematics
ISBN : 0470994541

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Bayesian Networks by Olivier Pourret,Patrick Naïm,Bruce Marcot Pdf

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.

Author : S.-L. Sun,A.J. Tallón-Ballesteros,D.S. Pamučar
Publisher : IOS Press
Page : 652 pages
File Size : 42,6 Mb
Release : 2016-11-24
Category : Computers
ISBN : 9781614997221

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Fuzzy Systems and Data MiningII by S.-L. Sun,A.J. Tallón-Ballesteros,D.S. Pamučar Pdf

Fuzzy systems and data mining are now an essential part of information technology and data management, with applications affecting every imaginable aspect of our daily lives. This book contains 81 selected papers from those accepted and presented at the 2nd international conference on Fuzzy Systems and Data Mining (FSDM2016), held in Macau, China, in December 2016. This annual conference focuses on 4 main groups of topics: fuzzy theory, algorithm and system; fuzzy applications; the interdisciplinary field of fuzzy logic and data mining; and data mining, and the event provided a forum where more than 100 qualified, high-level researchers and experts from over 20 countries, including 4 keynote speakers, gathered to create an important platform for researchers and engineers worldwide to engage in academic communication. All the papers collected here present original ideas, methods and results of general significance supported by clear reasoning and compelling evidence, and as such the book represents a valuable and wide ranging reference resource of interest to all those whose work involves fuzzy systems and data mining.

Author : Sik-Yum Lee,Xin-Yuan Song
Publisher : John Wiley & Sons
Page : 396 pages
File Size : 45,6 Mb
Release : 2012-07-05
Category : Mathematics
ISBN : 9781118358870

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Basic and Advanced Bayesian Structural Equation Modeling by Sik-Yum Lee,Xin-Yuan Song Pdf

This book provides clear instructions to researchers on how to apply Structural Equation Models (SEMs) for analyzing the inter relationships between observed and latent variables. Basic and Advanced Bayesian Structural Equation Modeling introduces basic and advanced SEMs for analyzing various kinds of complex data, such as ordered and unordered categorical data, multilevel data, mixture data, longitudinal data, highly non-normal data, as well as some of their combinations. In addition, Bayesian semiparametric SEMs to capture the true distribution of explanatory latent variables are introduced, whilst SEM with a nonparametric structural equation to assess unspecified functional relationships among latent variables are also explored. Statistical methodologies are developed using the Bayesian approach giving reliable results for small samples and allowing the use of prior information leading to better statistical results. Estimates of the parameters and model comparison statistics are obtained via powerful Markov Chain Monte Carlo methods in statistical computing. Introduces the Bayesian approach to SEMs, including discussion on the selection of prior distributions, and data augmentation. Demonstrates how to utilize the recent powerful tools in statistical computing including, but not limited to, the Gibbs sampler, the Metropolis-Hasting algorithm, and path sampling for producing various statistical results such as Bayesian estimates and Bayesian model comparison statistics in the analysis of basic and advanced SEMs. Discusses the Bayes factor, Deviance Information Criterion (DIC), and $L_\nu$-measure for Bayesian model comparison. Introduces a number of important generalizations of SEMs, including multilevel and mixture SEMs, latent curve models and longitudinal SEMs, semiparametric SEMs and those with various types of discrete data, and nonparametric structural equations. Illustrates how to use the freely available software WinBUGS to produce the results. Provides numerous real examples for illustrating the theoretical concepts and computational procedures that are presented throughout the book. Researchers and advanced level students in statistics, biostatistics, public health, business, education, psychology and social science will benefit from this book.

Author : Brown, Mitchell,Nordyke, Shane,Thies, Cameron G.
Publisher : Edward Elgar Publishing
Page : 369 pages
File Size : 49,7 Mb
Release : 2022-09-06
Category : Political Science
ISBN : 9781800885288

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Teaching Graduate Political Methodology by Brown, Mitchell,Nordyke, Shane,Thies, Cameron G. Pdf

Providing expert advice from established scholars in the field of political science, this engaging companion book to Teaching Undergraduate Political Methodology imparts informative guidance on teaching research methods across the graduate curriculum. Written in a concise yet comprehensive style, it illustrates practical and conceptual advice, alongside more detailed chapters focussing on the different aspects of teaching political methodology.

Author : Carlos Fernandez-Lozano
Publisher : MDPI
Page : 314 pages
File Size : 41,9 Mb
Release : 2021-04-28
Category : Science
ISBN : 9783036509440

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Statistical Inference from High Dimensional Data by Carlos Fernandez-Lozano Pdf

• Real-world problems can be high-dimensional, complex, and noisy • More data does not imply more information • Different approaches deal with the so-called curse of dimensionality to reduce irrelevant information • A process with multidimensional information is not necessarily easy to interpret nor process • In some real-world applications, the number of elements of a class is clearly lower than the other. The models tend to assume that the importance of the analysis belongs to the majority class and this is not usually the truth • The analysis of complex diseases such as cancer are focused on more-than-one dimensional omic data • The increasing amount of data thanks to the reduction of cost of the high-throughput experiments opens up a new era for integrative data-driven approaches • Entropy-based approaches are of interest to reduce the dimensionality of high-dimensional data

Author : Dirk Husmeier,Richard Dybowski,Stephen Roberts
Publisher : Springer Science & Business Media
Page : 511 pages
File Size : 43,5 Mb
Release : 2006-05-06
Category : Computers
ISBN : 9781846281198

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Probabilistic Modeling in Bioinformatics and Medical Informatics by Dirk Husmeier,Richard Dybowski,Stephen Roberts Pdf

Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies.