Decision Graphs
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Bayesian Networks And Decision Graphs
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Author : Thomas Dyhre Nielsen
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-03-17
Bayesian Networks And Decision Graphs written by Thomas Dyhre Nielsen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-03-17 with Science categories.
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.
Lists Decisions And Graphs
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Author :
language : en
Publisher: S. Gill Williamson
Release Date :
Lists Decisions And Graphs written by and has been published by S. Gill Williamson this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Decision Graphs
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Author : Jonathan Oliver
language : en
Publisher:
Release Date : 1992
Decision Graphs written by Jonathan Oliver and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Artificial intelligence categories.
Abstract: "In this paper, we examine Decision Graphs, a generalization of decision trees. We present an inference scheme to construct decision graphs using the Minimum Message Length Principle. Empirical tests demonstrate that this scheme compares favourably with other decision tree inference schemes. This work provides a metric for comparing the relative merit of the decision tree and decision graph formalisms for a particular domain."
From Decision Trees To Decision Graphs
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Author : Mekhon Ṿaitsman le-madaʻ. Dept. of Applied Mathematics and Computer Science
language : en
Publisher:
Release Date : 1990
From Decision Trees To Decision Graphs written by Mekhon Ṿaitsman le-madaʻ. Dept. of Applied Mathematics and Computer Science and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Logic programming categories.
When decision trees are exponential the corresponding decision graphs, in the worst case, degenerate to WAM code. In this paper we describe the decision graph principles and compilation algorithm and present experimental results comparing decision graphs to decision trees. A compiler based on the decision graph method has been implemented. Measuring real large programs reveals substantial savings in code size relative to the decision trees and substantial speedup in run time relative to the WAM-like compilation method."
Bayesian Networks And Decision Graphs
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Author :
language : en
Publisher:
Release Date : 2001
Bayesian Networks And Decision Graphs written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Bayesian statistical decision theory categories.
Bayesian networks and decision graphs are formal graphical languages for representation and communication of decision scenarios requiring reasoning under uncertainty. Their strengths are two-sided. It is easy for humans to construct and to understand them, and when communicated to a computer, they can easily be compiled. Furthermore, handy algorithms are developed for analyses of the models and for providing responses to a wide range of requests such as belief updating, determining optimal strategies, conflict analyses of evidence, and most probable explanation. The book emphasizes both the human and the computer sides. Part I gives a thorough introduction to Bayesian networks as well as decision trees and infulence diagrams, and through examples and exercises, the reader is instructed in building graphical models from domain knowledge. This part is self-contained and it does not require other background than standard secondary school mathematics. Part II is devoted to the presentation of algorithms and complexity issues. This part is also self-contained, but it requires that the reader is familiar with working with texts in the mathematical language. The author also: - provides a well-founded practical introduction to Bayesian networks, decision trees and influence diagrams; - gives several examples and exercises exploiting the computer systems for Bayesian netowrks and influence diagrams; - gives practical advice on constructiong Bayesian networks and influence diagrams from domain knowledge; - embeds decision making into the framework of Bayesian networks; - presents in detail the currently most efficient algorithms for probability updating in Bayesian networks; - discusses a wide range of analyes tools and model requests together with algorithms for calculation of responses; - gives a detailed presentation of the currently most efficient algorithm for solving influence diagrams.
Interactive Decision Making
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Author : Liping Fang
language : en
Publisher: John Wiley & Sons
Release Date : 1993-10-18
Interactive Decision Making written by Liping Fang and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-10-18 with Technology & Engineering categories.
A comprehensive procedure for systematically examining actual disputes. Clearly explains the theory and practice of this novel approach to conflict modeling, analysis and resolution. Based upon ideas from both graph and game theories, it extends the realm of multiple objective-multiple-participant decision making in useful directions. Includes a wealth of illustrations and a computer disk.
Decision Graphs For Information Process
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Author : Wataru Mayeda
language : en
Publisher:
Release Date : 1973
Decision Graphs For Information Process written by Wataru Mayeda and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1973 with categories.
Identifying and classifying information are important tasks in many areas such as data processing in census studies, process controls in information processing systems, the recognition of patterns, and so on. Here the author develops a procedure to design a reasonable testing process to identify information from a given decision table. There are several papers dealing with decision trees and decision tables. In the paper, the author attacks the problem by the use of linear graph theory so that more general cases of identifying information can be covered. (Modified author abstract).
Inferring Decision Graphs
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Author : Jonathan Oliver
language : en
Publisher:
Release Date : 1992
Inferring Decision Graphs written by Jonathan Oliver and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Artificial intelligence categories.
Abstract: "In this paper, we introduce Decision Graphs, a generalization of decision trees. We present an inference scheme to construct Decision Graphs using the Minimum Message Length Principle. Empirical tests demonstrate that this scheme compares favourably with other decision tree inference schemes."
Wrappers For Performance Enhancement And Oblivious Decision Graphs
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Author : Ron Kohavi
language : en
Publisher:
Release Date : 1995
Wrappers For Performance Enhancement And Oblivious Decision Graphs written by Ron Kohavi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computer algorithms categories.
Applications Of Zero Suppressed Decision Diagrams
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Author : Jon T. Butler
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Applications Of Zero Suppressed Decision Diagrams written by Jon T. Butler and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Technology & Engineering categories.
A zero-suppressed decision diagram (ZDD) is a data structure to represent objects that typically contain many zeros. Applications include combinatorial problems, such as graphs, circuits, faults, and data mining. This book consists of four chapters on the applications of ZDDs. The first chapter by Alan Mishchenko introduces the ZDD. It compares ZDDs to BDDs, showing why a more compact representation is usually achieved in a ZDD. The focus is on sets of subsets and on sum-of-products (SOP) expressions. Methods to generate all the prime implicants (PIs), and to generate irredundant SOPs are shown. A list of papers on the applications of ZDDs is also presented. In the appendix, ZDD procedures in the CUDD package are described. The second chapter by Tsutomu Sasao shows methods to generate PIs and irredundant SOPs using a divide and conquer method. This chapter helps the reader to understand the methods presented in the first chapter. The third chapter by Shin-Ichi Minato introduces the ""frontier-based"" method that efficiently enumerates certain subsets of a graph. The final chapter by Shinobu Nagayama shows a method to match strings of characters. This is important in routers, for example, where one must match the address information of an internet packet to the proprer output port. It shows that ZDDs are more compact than BDDs in solving this important problem. Each chapter contains exercises, and the appendix contains their solutions. Table of Contents: Preface / Acknowledgments / Introduction to Zero-Suppressed Decision Diagrams / Efficient Generation of Prime Implicants and Irredundant Sum-of-Products Expressions / The Power of Enumeration--BDD/ZDD-Based Algorithms for Tackling Combinatorial Explosion / Regular Expression Matching Using Zero-Suppressed Decision Diagrams / Authors' and Editors' Biographies / Index