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Incomplete Information: Rough Set Analysis, Ewa Orlowska


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Автор: Ewa Orlowska
Название:  Incomplete Information: Rough Set Analysis
ISBN: 9783790824575
Издательство: Springer
Классификация:



ISBN-10: 3790824577
Обложка/Формат: Paperback
Страницы: 613
Вес: 0.87 кг.
Дата издания: 21.10.2010
Серия: Studies in Fuzziness and Soft Computing
Язык: English
Размер: 234 x 156 x 32
Основная тема: Computer Science
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: In 1982, Professor Pawlak published his seminal paper on what he called rough sets - a work which opened a new direction in the development of theories of incomplete information.

Preferences and Decisions under Incomplete Knowledge

Автор: Janos Fodor; Bernard De Baets; Patrice Perny
Название: Preferences and Decisions under Incomplete Knowledge
ISBN: 3790813036 ISBN-13(EAN): 9783790813036
Издательство: Springer
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Цена: 158380.00 T
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Описание: Decision problems are pervaded with incomplete knowledge - imprecision and/or uncertain information, both in the problem description and in the preferential information. This volume addresses various theoretical and practical aspects related to the handling of this incompleteness.

Information Systems Analysis and Modeling

Автор: Vladimir S. Lerner
Название: Information Systems Analysis and Modeling
ISBN: 1461370981 ISBN-13(EAN): 9781461370987
Издательство: Springer
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Цена: 139750.00 T
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Описание: Informational Macrodynamics (IMD) presents the unified information systemic approach with common information language for modeling, analysis and optimization of a variety of interactive processes, such as physical, biological, economical, social, and informational, including human activities.

Bayesian Full Information Analysis of Simultaneous Equation Models Using Integration by Monte Carlo

Автор: L. Bauwens
Название: Bayesian Full Information Analysis of Simultaneous Equation Models Using Integration by Monte Carlo
ISBN: 3540133844 ISBN-13(EAN): 9783540133841
Издательство: Springer
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Цена: 102480.00 T
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Описание: In their review of the "Bayesian analysis of simultaneous equation systems", Dr ze and Richard (1983) - hereafter DR - express the following viewpoint about the present state of development of the Bayesian full information analysis of such sys- tems i) the method allows "a flexible specification of the prior density, including well defined noninformative prior measures"; ii) it yields "exact finite sample posterior and predictive densities". However, they call for further developments so that these densities can be eval- uated through 'numerical methods, using an integrated software packa e. To that end, they recommend the use of a Monte Carlo technique, since van Dijk and Kloek (1980) have demonstrated that "the integrations can be done and how they are done". In this monograph, we explain how we contribute to achieve the developments suggested by Dr ze and Richard. A basic idea is to use known properties of the porterior density of the param- eters of the structural form to design the importance functions, i. e. approximations of the posterior density, that are needed for organizing the integrations.

Incomplete Information: Rough Set Analysis

Автор: Ewa Orlowska
Название: Incomplete Information: Rough Set Analysis
ISBN: 3790810495 ISBN-13(EAN): 9783790810493
Издательство: Springer
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Цена: 181670.00 T
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Описание: This is an account of the current status of the basic theory, extensions and applications of rough sets. The book presents rough set formalisms and methods of modelling and handling incomplete information, and motivates their applicability to knowledge discovery and machine learning.

Litigation and Settlement in a Game with Incomplete Information

Автор: Wolfgang Ryll
Название: Litigation and Settlement in a Game with Incomplete Information
ISBN: 3540613048 ISBN-13(EAN): 9783540613046
Издательство: Springer
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Цена: 71730.00 T
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Описание: We can distinguish between games which focus on strategic elements like games with incomplete information (see, for example, P`ng (1983), Samuelson (1982) and Schweizer (1989" and decision-theoretic models neglecting strategic elements (see, for example, Landes (1971) and Gould (1973".

The Purification Problem for Constrained Games with Incomplete Information

Автор: Helmut Meister
Название: The Purification Problem for Constrained Games with Incomplete Information
ISBN: 3540184295 ISBN-13(EAN): 9783540184294
Издательство: Springer
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Цена: 102480.00 T
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Описание: The approach presented in this book combines two aspects of generalizations of the noncooperative game as developed by Nash.

Incomplete Information: Structure, Inference, Complexity

Автор: Stephane P. Demri; Ewa Orlowska
Название: Incomplete Information: Structure, Inference, Complexity
ISBN: 3642075401 ISBN-13(EAN): 9783642075407
Издательство: Springer
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Цена: 153720.00 T
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Описание: This monograph presents a systematic, exhaustive and up-to-date overview of formal methods and theories for data analysis and inference inspired by the concept of rough set. The formalisms developed are non-invasive in that only the actual information that is needed in the process of analysis without external sources of information being required.

International Migration Under Incomplete Information

Автор: Siegfried Berninghaus; Hans G. Seifert-Vogt
Название: International Migration Under Incomplete Information
ISBN: 3662027240 ISBN-13(EAN): 9783662027240
Издательство: Springer
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Цена: 46570.00 T
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Описание: It is the main purpose of the book to give a logically consistent foundation of migration decision making under incomplete information in a unified framework. Decision rules for migration are derived from a general model of Stochastic Dynamic Programming and the properties of temporary migration equilibria are discussed as well.

Preferences and Decisions under Incomplete Knowledge

Автор: Janos Fodor; Bernard De Baets; Patrice Perny
Название: Preferences and Decisions under Incomplete Knowledge
ISBN: 3790824747 ISBN-13(EAN): 9783790824742
Издательство: Springer
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Цена: 158380.00 T
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Описание: Nowadays, decision problems are pervaded with incomplete knowledge, i.e., imprecision and/or uncertain information, both in the problem description and in the preferential information.

Bayesian Full Information Structrual Analysis

Автор: J.A. Morales
Название: Bayesian Full Information Structrual Analysis
ISBN: 3540054170 ISBN-13(EAN): 9783540054177
Издательство: Springer
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Цена: 102480.00 T
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Описание: 1 1. Statement of the problem. Bayes' theorem provides a very powerful tool for statistical inference, especially when pooling information from different sources is appropriate. Thus, prior information resulting from economic theory and/or from previous (real or hypothetical) samples can be combined with the information embodied in new observations; and this operation can be performed formally, within a rigorous mathematical framework. To introduce the Bayesian analysis of the simultaneous equations model, we shall base our presentation in the very convenient exposition given by Dreze in his presidential adress to the . S' 2 C f Second World ongress 0 the Econometr1c oC1ety. The Bayesian method in statistics is usually presented as follows Consider the joint probability density function f(x.e) defined on the product space X x9, where X = {x} denotes the sample space, and e = {e} denotes the parameter space, If we decompose the joint density f(x, e) in a conditional density f(x/e) and a marginal lThe beginning of this section reviews some very well known proposi- tions of Bayesian analysis. Those who are familiar with the subject can skip this part, and start with p.5. 2J.H.Dreze. "Econometrics and Decision Theory." Presidential adress delivered at the Second World Congress of the Econometric Society.

Heterogeneous Information Network Analysis and Applications

Автор: Chuan Shi; Philip S. Yu
Название: Heterogeneous Information Network Analysis and Applications
ISBN: 3319562118 ISBN-13(EAN): 9783319562117
Издательство: Springer
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Цена: 111790.00 T
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Описание: This information will help researchers to understand how to analyze networked data with heterogeneous information networks.

Intelligent Technologies for Information Analysis

Автор: Ning Zhong; Jiming Liu
Название: Intelligent Technologies for Information Analysis
ISBN: 3642073786 ISBN-13(EAN): 9783642073786
Издательство: Springer
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Цена: 144410.00 T
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Описание: Intelligent Information Technology (iiT) encompasses the theories and ap- plications of artificial intelligence, statistical pattern recognition, learning theory, data warehousing, data mining and knowledge discovery, Grid com- puting, and autonomous agents and multi-agent systems in the context of today's as well as future IT, such as Electronic Commerce (EC), Business Intelligence (BI), Social Intelligence (SI), Web Intelligence (WI), Knowledge Grid (KG), and Knowledge Community (KC), among others. The multi-author monograph presents the current state of the research and development in intelligent technologies for information analysis, in par- ticular, advances in agents, data mining, and learning theory, from both the- oretical and application aspects. It investigates the future of information technology (IT) from a new intelligent IT (iiT) perspective, and highlights major iiT-related topics by structuring an introductory chapter and 22 sur- vey/research chapters into 5 parts: (1) emerging data mining technology, (2) data mining for Web intelligence, (3) emerging agent technology, ( 4) emerging soft computing technology, and (5) statistical learning theory. Each chapter includes the original work of the author(s) as well as a comprehensive survey related to the chapter's topic. This book will become a valuable source of reference for R&D profession- als active in advanced intelligent information technologies. Students as well as IT professionals and ambitious practitioners concerned with advanced in- telligent information technologies will appreciate the book as a useful text enhanced by numerous illustrations and examples.


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