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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 Decision Analysis

contains basic material on subjective probability theory and multi-attribute utility theory, event and decision trees, Bayesian networks, influence;

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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 Networks

, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips;

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Chain Event Graphs

analysis and has written two other books, most recently Bayesian Decision Analysis: Principles and Practice (Cambridge University Press 2010).;

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Chain Event Graphs

field of statistics, AI, and decision analysis and has written two other books, most recently Bayesian Decision Analysis: Principles and;

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Risk Assessment and Decision Analysis with Bayesian Networks

practical real-world problem solving and model building, as opposed to algorithms and theory, Risk Assessment and Decision Analysis with Bayesian;

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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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Symbolic and Quantitative Approaches to Reasoning with Uncertainty

were carefully reviewed and selected from 63 submissions and cover topics on analogical reasoning; argumentation; Bayesian networks; belief;

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Probabilistic Graphical Models

of Bayesian classifiers, hidden Markov models, Bayesian networks, dynamic and temporal Bayesian networks, Markov random fields, influence diagrams;

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Risk Assessment and Decision Analysis with Bayesian Networks

to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide more powerful insights and better;

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Probabilistic Graphical Models

, highlighting the many uses of Bayesian classifiers, hidden Markov models, Bayesian networks, dynamic and temporal Bayesian networks, Markov random;

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Probabilistic Graphical Models

, highlighting the many uses of Bayesian classifiers, hidden Markov models, Bayesian networks, dynamic and temporal Bayesian networks, Markov random;

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Machine Learning

squares and maximum likelihood methods, ridge regression, Bayesian decision theory classification, logistic regression, and decision trees. It;

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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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Statistical Decision Theory and Bayesian Analysis

as empirical and hierarchical Bayes analysis, Bayesian calculation, Bayesian communication, and group decision making. With these changes;

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Computational Learning And Probabilistic Reasoning

statistical analysis. Part III includes case studies and descriptions of Bayesian Belief Networks and Hybrid Systems. Finally, Part IV on Decision;

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Managing Data Mining Technologies in Organizations

, medical diagnosis, genetic algorithms, Bayesian networks, neural networks, and many others. The chapters discuss research results and applications;

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Market Research and Modeling: Progress and Prospects

in marketing and marketing research. This work emphasizes new developments in Bayesian Decision Analysis, Multivariate Analysis, Multidimensional;

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Cambridge Studies in Probability, Induction and Decision Theory

This important collection of essays is a synthesis of foundational studies in Bayesian decision theory and statistics. An overarching topic;

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Rethinking the Foundations of Statistics

This important collection of essays is a synthesis of foundational studies in Bayesian decision theory and statistics. An overarching topic;

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Rational Decisions

of scientific discovery and macroeconomic enterprise. When is it correct to use Bayesian decision theory--and when does it need to be modified? Using a;

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Cooperative and Graph Signal Processing

basics of adaptation and learning in networks, the essentials of detection, estimation and filtering, Bayesian inference in networks;

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Bayesian Networks and Influence Diagrams

Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for;

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Probabilistic Methods for Bioinformatics

The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability;

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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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