Machine Learning And Probabilistic Graphical Models For Decision Support Systems

Download Machine Learning And Probabilistic Graphical Models For Decision Support Systems full books in PDF, epub, and Kindle. Read online Machine Learning And Probabilistic Graphical Models For Decision Support Systems ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Machine Learning and Probabilistic Graphical Models for Decision Support Systems

Author : Kim Phuc Tran
Publisher : CRC Press
ISBN 13 : 100077144X
Total Pages : 330 pages
Book Rating : 4.0/5 (7 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning and Probabilistic Graphical Models for Decision Support Systems by : Kim Phuc Tran

Download or read book Machine Learning and Probabilistic Graphical Models for Decision Support Systems written by Kim Phuc Tran and published by CRC Press. This book was released on 2022-10-13 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions. It explores Bayesian network learning, Control Chart, Reinforcement Learning for multicriteria DSS, Anomaly Detection in Smart Manufacturing with Federated Learning, DSS in healthcare, DSS for supply chain management, etc. Researchers and practitioners alike will benefit from this book to enhance the understanding of machine learning, Probabilistic Graphical Models, and their uses in DSS in the context of decision making with uncertainty. The real-world case studies in various fields with guidance and recommendations for the practical applications of these studies are introduced in each chapter.

Probabilistic Graphical Models

Author : Daphne Koller
Publisher : MIT Press
ISBN 13 : 0262258358
Total Pages : 1270 pages
Book Rating : 4.2/5 (622 download)

DOWNLOAD NOW!

Book Synopsis Probabilistic Graphical Models by : Daphne Koller

Download or read book Probabilistic Graphical Models written by Daphne Koller and published by MIT Press. This book was released on 2009-07-31 with total page 1270 pages. Available in PDF, EPUB and Kindle. Book excerpt: A general framework for constructing and using probabilistic models of complex systems that would enable a computer to use available information for making decisions. Most tasks require a person or an automated system to reason—to reach conclusions based on available information. The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality. Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

Probabilistic Graphical Models

Author : Luis Enrique Sucar
Publisher : Springer Nature
ISBN 13 : 3030619435
Total Pages : 370 pages
Book Rating : 4.0/5 (36 download)

DOWNLOAD NOW!

Book Synopsis Probabilistic Graphical Models by : Luis Enrique Sucar

Download or read book Probabilistic Graphical Models written by Luis Enrique Sucar and published by Springer Nature. This book was released on 2020-12-23 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fully updated new edition of a uniquely accessible textbook/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective. It features new material on partially observable Markov decision processes, causal graphical models, causal discovery and deep learning, as well as an even greater number of exercises; it also incorporates a software library for several graphical models in Python. The book covers the fundamentals for each of the main classes of PGMs, including representation, inference and learning principles, and reviews real-world applications for each type of model. These applications are drawn from a broad range of disciplines, highlighting the many uses of Bayesian classifiers, hidden Markov models, Bayesian networks, dynamic and temporal Bayesian networks, Markov random fields, influence diagrams, and Markov decision processes. Topics and features: Presents a unified framework encompassing all of the main classes of PGMs Explores the fundamental aspects of representation, inference and learning for each technique Examines new material on partially observable Markov decision processes, and graphical models Includes a new chapter introducing deep neural networks and their relation with probabilistic graphical models Covers multidimensional Bayesian classifiers, relational graphical models, and causal models Provides substantial chapter-ending exercises, suggestions for further reading, and ideas for research or programming projects Describes classifiers such as Gaussian Naive Bayes, Circular Chain Classifiers, and Hierarchical Classifiers with Bayesian Networks Outlines the practical application of the different techniques Suggests possible course outlines for instructors This classroom-tested work is suitable as a textbook for an advanced undergraduate or a graduate course in probabilistic graphical models for students of computer science, engineering, and physics. Professionals wishing to apply probabilistic graphical models in their own field, or interested in the basis of these techniques, will also find the book to be an invaluable reference. Dr. Luis Enrique Sucar is a Senior Research Scientist at the National Institute for Astrophysics, Optics and Electronics (INAOE), Puebla, Mexico. He received the National Science Prize en 2016.

Machine Learning and Probabilistic Graphical Models for Decision Support Systems

Author : Kim Phuc Tran
Publisher : CRC Press
ISBN 13 : 9781000771466
Total Pages : 0 pages
Book Rating : 4.7/5 (714 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning and Probabilistic Graphical Models for Decision Support Systems by : Kim Phuc Tran

Download or read book Machine Learning and Probabilistic Graphical Models for Decision Support Systems written by Kim Phuc Tran and published by CRC Press. This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions. It explores Bayesian network learning, Control Chart, Reinforcement Learning for multicriteria DSS, Anomaly Detection in Smart Manufacturing with Federated Learning, DSS in healthcare, DSS for supply chain management, etc. Researchers and practitioners alike will benefit from this book to enhance the understanding of machine learning, Probabilistic Graphical Models, and their uses in DSS in the context of decision making with uncertainty. The real-world case studies in various fields with guidance and recommendations for the practical applications of these studies are introduced in each chapter.

Bayesian Reasoning and Machine Learning

Author : David Barber
Publisher : Cambridge University Press
ISBN 13 : 0521518148
Total Pages : 739 pages
Book Rating : 4.5/5 (215 download)

DOWNLOAD NOW!

Book Synopsis Bayesian Reasoning and Machine Learning by : David Barber

Download or read book Bayesian Reasoning and Machine Learning written by David Barber and published by Cambridge University Press. This book was released on 2012-02-02 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical introduction perfect for final-year undergraduate and graduate students without a solid background in linear algebra and calculus.

Learning in Graphical Models

Author : M.I. Jordan
Publisher : Springer Science & Business Media
ISBN 13 : 9401150141
Total Pages : 658 pages
Book Rating : 4.4/5 (11 download)

DOWNLOAD NOW!

Book Synopsis Learning in Graphical Models by : M.I. Jordan

Download or read book Learning in Graphical Models written by M.I. Jordan and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 658 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past decade, a number of different research communities within the computational sciences have studied learning in networks, starting from a number of different points of view. There has been substantial progress in these different communities and surprising convergence has developed between the formalisms. The awareness of this convergence and the growing interest of researchers in understanding the essential unity of the subject underlies the current volume. Two research communities which have used graphical or network formalisms to particular advantage are the belief network community and the neural network community. Belief networks arose within computer science and statistics and were developed with an emphasis on prior knowledge and exact probabilistic calculations. Neural networks arose within electrical engineering, physics and neuroscience and have emphasised pattern recognition and systems modelling problems. This volume draws together researchers from these two communities and presents both kinds of networks as instances of a general unified graphical formalism. The book focuses on probabilistic methods for learning and inference in graphical models, algorithm analysis and design, theory and applications. Exact methods, sampling methods and variational methods are discussed in detail. Audience: A wide cross-section of computationally oriented researchers, including computer scientists, statisticians, electrical engineers, physicists and neuroscientists.

Bayesian Networks and Decision Graphs

Author : Thomas Dyhre Nielsen
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.

Intelligent Computing Systems and Applications

Author : Sivaji Bandyopadhyay
Publisher : Springer Nature
ISBN 13 : 9819754127
Total Pages : 600 pages
Book Rating : 4.8/5 (197 download)

DOWNLOAD NOW!

Book Synopsis Intelligent Computing Systems and Applications by : Sivaji Bandyopadhyay

Download or read book Intelligent Computing Systems and Applications written by Sivaji Bandyopadhyay and published by Springer Nature. This book was released on with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Computational Intelligence in Data Science

Author : Mieczyslaw Lech Owoc
Publisher : Springer Nature
ISBN 13 : 3031699866
Total Pages : 532 pages
Book Rating : 4.0/5 (316 download)

DOWNLOAD NOW!

Book Synopsis Computational Intelligence in Data Science by : Mieczyslaw Lech Owoc

Download or read book Computational Intelligence in Data Science written by Mieczyslaw Lech Owoc and published by Springer Nature. This book was released on with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Artificial Intelligence for Smart Manufacturing

Author : Kim Phuc Tran
Publisher : Springer Nature
ISBN 13 : 3031305108
Total Pages : 271 pages
Book Rating : 4.0/5 (313 download)

DOWNLOAD NOW!

Book Synopsis Artificial Intelligence for Smart Manufacturing by : Kim Phuc Tran

Download or read book Artificial Intelligence for Smart Manufacturing written by Kim Phuc Tran and published by Springer Nature. This book was released on 2023-06-01 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a comprehensive overview of the latest developments in the field of smart manufacturing, exploring theoretical research, technological advancements, and practical applications of AI approaches. With Industry 4.0 paving the way for intelligent systems and innovative technologies to enhance productivity and quality, the transition to Industry 5.0 has introduced a new concept known as augmented intelligence (AuI), combining artificial intelligence (AI) with human intelligence (HI). As the demand for smart manufacturing continues to grow, this book serves as a valuable resource for professionals and practitioners looking to stay up-to-date with the latest advancements in Industry 5.0. Covering a range of important topics such as product design, predictive maintenance, quality control, digital twin, wearable technology, quantum, and machine learning, the book also features insightful case studies that demonstrate the practical application of these tools in real-world scenarios. Overall, this book provides a comprehensive and up-to-date account of the latest advancements in smart manufacturing, offering readers a valuable resource for navigating the challenges and opportunities presented by Industry 5.0.

MEDINFO 2015: EHealth-enabled Health

Author : I.N. Sarkar
Publisher : IOS Press
ISBN 13 : 1614995648
Total Pages : 1180 pages
Book Rating : 4.6/5 (149 download)

DOWNLOAD NOW!

Book Synopsis MEDINFO 2015: EHealth-enabled Health by : I.N. Sarkar

Download or read book MEDINFO 2015: EHealth-enabled Health written by I.N. Sarkar and published by IOS Press. This book was released on 2015-08-12 with total page 1180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Health and Biomedical Informatics is a rapidly evolving multidisciplinary field; one in which new developments may prove crucial in meeting the challenge of providing cost-effective, patient-centered healthcare worldwide. This book presents the proceedings of MEDINFO 2015, held in São Paulo, Brazil, in August 2015. The theme of this conference is ‘eHealth-enabled Health’, and the broad spectrum of topics covered ranges from emerging methodologies to successful implementations of innovative applications, integration and evaluation of eHealth systems and solutions. Included here are 178 full papers and 248 poster abstracts, selected after a rigorous review process from nearly 800 submissions by 2,500 authors from 59 countries. The conference brings together researchers, clinicians, technologists and managers from all over the world to share their experiences on the use of information methods, systems and technologies to promote patient-centered care, improving patient safety, enhancing care outcomes, facilitating translational research and enabling precision medicine, as well as advancing education and skills in Health and Biomedical Informatics. This comprehensive overview of Health and Biomedical Informatics will be of interest to all those involved in designing, commissioning and providing healthcare, wherever they may be.

Cybersecurity and Data Management Innovations for Revolutionizing Healthcare

Author : Murugan, Thangavel
Publisher : IGI Global
ISBN 13 :
Total Pages : 402 pages
Book Rating : 4.3/5 (693 download)

DOWNLOAD NOW!

Book Synopsis Cybersecurity and Data Management Innovations for Revolutionizing Healthcare by : Murugan, Thangavel

Download or read book Cybersecurity and Data Management Innovations for Revolutionizing Healthcare written by Murugan, Thangavel and published by IGI Global. This book was released on 2024-07-23 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: In todays digital age, the healthcare industry is undergoing a paradigm shift towards embracing innovative technologies to enhance patient care, improve efficiency, and ensure data security. With the increasing adoption of electronic health records, telemedicine, and AI-driven diagnostics, robust cybersecurity measures and advanced data management strategies have become paramount. Protecting sensitive patient information from cyber threats is critical and maintaining effective data management practices is essential for ensuring the integrity, accuracy, and availability of vast amounts of healthcare data. Cybersecurity and Data Management Innovations for Revolutionizing Healthcare delves into the intersection of healthcare, data management, cybersecurity, and emerging technologies. It brings together a collection of insightful chapters that explore the transformative potential of these innovations in revolutionizing healthcare practices around the globe. Covering topics such as advanced analytics, data breach detection, and privacy preservation, this book is an essential resource for healthcare professionals, researchers, academicians, healthcare professionals, data scientists, cybersecurity experts, and more.

Intelligent Systems for Sustainable Person-Centered Healthcare

Author : Dalia Kriksciuniene
Publisher : Springer Nature
ISBN 13 : 3030793532
Total Pages : 256 pages
Book Rating : 4.0/5 (37 download)

DOWNLOAD NOW!

Book Synopsis Intelligent Systems for Sustainable Person-Centered Healthcare by : Dalia Kriksciuniene

Download or read book Intelligent Systems for Sustainable Person-Centered Healthcare written by Dalia Kriksciuniene and published by Springer Nature. This book was released on 2022 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Person-Centered Care (PCC) conceptual background of healthcare positions a person in the center of a healthcare system, instead of defining a patient as a set of diagnoses and treatment episodes. The PCC-based concep- tual background triggers enhanced application of Artificial Intelligence (AI), as it dissolves the limits of processing traditional medical data records. The ambition of taking care of a person health by knowing life conditions, values, and expectations for nurturing own health adds new dimensions for making PCC operational.

Innovations in Machine Learning and IoT for Water Management

Author : Kumar, Abhishek
Publisher : IGI Global
ISBN 13 :
Total Pages : 331 pages
Book Rating : 4.3/5 (693 download)

DOWNLOAD NOW!

Book Synopsis Innovations in Machine Learning and IoT for Water Management by : Kumar, Abhishek

Download or read book Innovations in Machine Learning and IoT for Water Management written by Kumar, Abhishek and published by IGI Global. This book was released on 2023-11-27 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: Water, our planet's life force, faces multiple challenges in the 21st century, including surging global demand, shifting climate patterns, and the urgent need for sustainable management. Guidance, knowledge, and hope is sharply needed in academia and technology industries, and Innovations in Machine Learning and IoT for Water Management is a formidable resource to provide these necessities. This book delves into the dynamic synergy of Artificial Intelligence (AI), Machine Learning (ML), and the Internet of Things (IoT), ushering in a new era of water resource stewardship. This book embarks on a journey through the frontiers of AI and IoT, unveiling their transformative impact on water management. From the vantage point of satellite imagery analysis, it scrutinizes the Earth's vital signs, unlocking crucial insights into water resources. It chronicles the rise of AI-powered predictive analytics, a revolutionary force propelling precision water usage and conservation. This book explains how IoT can be an effective tool to increase intelligence of our water systems. The book meticulously navigates through domains as diverse as aquifer monitoring, hydropower generation optimization, and predictive analytics for water consumption. This book caters to a diverse audience, from water management experts and environmental scientists to data science aficionados and IoT enthusiasts. Engineers seeking to reimagine the future of water systems, technology enthusiasts eager to delve into AI's potential, and individuals impassioned by preserving water will all find a well-needed resource in these pages.

Anticipating Future Business Trends: Navigating Artificial Intelligence Innovations

Author : Rim El Khoury
Publisher : Springer Nature
ISBN 13 : 3031635698
Total Pages : 580 pages
Book Rating : 4.0/5 (316 download)

DOWNLOAD NOW!

Book Synopsis Anticipating Future Business Trends: Navigating Artificial Intelligence Innovations by : Rim El Khoury

Download or read book Anticipating Future Business Trends: Navigating Artificial Intelligence Innovations written by Rim El Khoury and published by Springer Nature. This book was released on with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Modeling And Analysis Of Dependable Systems: A Probabilistic Graphical Model Perspective

Author : Luigi Portinale
Publisher : World Scientific
ISBN 13 : 9814612057
Total Pages : 270 pages
Book Rating : 4.8/5 (146 download)

DOWNLOAD NOW!

Book Synopsis Modeling And Analysis Of Dependable Systems: A Probabilistic Graphical Model Perspective by : Luigi Portinale

Download or read book Modeling And Analysis Of Dependable Systems: A Probabilistic Graphical Model Perspective written by Luigi Portinale and published by World Scientific. This book was released on 2015-06-09 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: The monographic volume addresses, in a systematic and comprehensive way, the state-of-the-art dependability (reliability, availability, risk and safety, security) of systems, using the Artificial Intelligence framework of Probabilistic Graphical Models (PGM). After a survey about the main concepts and methodologies adopted in dependability analysis, the book discusses the main features of PGM formalisms (like Bayesian and Decision Networks) and the advantages, both in terms of modeling and analysis, with respect to classical formalisms and model languages.Methodologies for deriving PGMs from standard dependability formalisms will be introduced, by pointing out tools able to support such a process. Several case studies will be presented and analyzed to support the suitability of the use of PGMs in the study of dependable systems.

Development of Clinical Decision Support Systems using Bayesian Networks

Author : Mario A. Cypko
Publisher : Springer Nature
ISBN 13 : 3658325941
Total Pages : 148 pages
Book Rating : 4.6/5 (583 download)

DOWNLOAD NOW!

Book Synopsis Development of Clinical Decision Support Systems using Bayesian Networks by : Mario A. Cypko

Download or read book Development of Clinical Decision Support Systems using Bayesian Networks written by Mario A. Cypko and published by Springer Nature. This book was released on 2020-11-30 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the development of clinical decision support systems based on Bayesian networks, Mario A. Cypko investigates comprehensive expert models of multidisciplinary clinical treatment decisions and solves challenges in their modeling. The presented methods, models and tools are developed in close and intensive cooperation between knowledge engineers and clinicians. In the course of this study, laryngeal cancer serves as an exemplary treatment decision. The reader is guided through a development process and new opportunities for research and development are opened up: in modeling and validation of workflows, guided modeling, semi-automated modeling, advanced Bayesian networks, model-user interaction, inter-institutional modeling and quality management.