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This title in other editions

Studies in Fuzziness and Soft Computing #13: Incomplete Information: Rough Set Analysis

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Synopses & Reviews

Publisher Comments:

The book presents rough set formalisms and methods of modeling and handling incomplete information and motivates their applicability to knowledge representation, knowledge discovery and machine learning. The book focuses on providing representational and inference mechanisms for dealing with two particular aspects of incompleteness, namely indiscernibility and similarity. Those manifestations of particular aspects of incompleteness are inherent in any data structure and any cognitive unit. Knowledge discovered from such an information is uncertain in that it can only be asserted with a tolerance. The methods developed in the book are capable of exposing the limits of that tolerance and of making reliable inferences in the environments where complete information is not available. The framework presented in the book is general and unrestrictive, and yet at the same time captures the relevant features of a great variety of the user's data.

Table of Contents

Introduction: What You Always Wanted to Know about Rough Sets.- Rough Sets and Decision Rules: Synthesis of Decision Rules for Object Classification; On the Lower Boundaries in Learning Rules from Examples; On the Best Search Method in the LEM1 and LEM2 Algorithms.- Algebraic Structure of Rough Set Systems: Rough Sets and Algebras of Relations; Rough Set Theory and Logic-Algebraic Structures.- Dependence Spaces: Dependence Spaces of Information Systems; Applications of Dependence Spaces.- Reasoning About Constraints: Indiscernibility-Based Formalization of Dependencies in Information Systems; Dependencies between Many-Valued Attributes.- Indiscernibility-Based Reasoning: Logical Analysis of Indiscernibility; Some Philosophical Aspects of Indiscernibility; Rough Mereology and Anayltical Morphology.- Similarity-Based Reasoning: Similarity Versus Preference in Fuzzy-Based Logics; A Logic for Reasoning about Similarity; Information Systems, Similarity Relations and Modal Logics.- Extended Rough Set-Based Deduction Methods: Axiomatization of Logics Based on Kripke Models with Relative Accessibility Relations; Rough Logics: A Survey with Further Directions; On the Logic with Rough Quantifier.

Product Details

ISBN:
9783790824575
Author:
Orlowska, Ewa
Publisher:
Physica-Verlag
Location:
Heidelberg
Subject:
Computer Science
Subject:
Fuzzy-Logik
Subject:
Economics, finance, business and industry
Subject:
uuml;nstliche Intelligenz
Subject:
Rough sets.
Subject:
Unvollst
Subject:
ntilde;ndige Information
Subject:
Artificial Intelligence
Subject:
Fuzzy logic
Subject:
Incomplete Information
Subject:
Theory of computation
Subject:
Artificial Intelligence (incl. Robotics)
Subject:
Game Theory/Mathematical Methods
Subject:
Operations Research/Decision Theory
Subject:
Operating Systems - General
Subject:
Knstliche Intelligenz
Subject:
Unvollständige Information
Subject:
Operation Research/Decision Theory
Subject:
Language, literature and biography
Subject:
Engineering
Subject:
Information Theory
Subject:
Economics, mathematical
Subject:
Operations Research
Copyright:
Edition Description:
Softcover reprint of hardcover 1st ed. 1998
Series:
Studies in Fuzziness and Soft Computing
Series Volume:
13
Publication Date:
20101201
Binding:
TRADE PAPER
Language:
English
Pages:
625
Dimensions:
235 x 155 mm 930 gr

Related Subjects

Computers and Internet » Artificial Intelligence » General
Computers and Internet » Computers Reference » General
Computers and Internet » Operating Systems » General
Computers and Internet » Personal Computers » General
Health and Self-Help » Health and Medicine » Medical Specialties
Science and Mathematics » Geology » Earth Sciences
Science and Mathematics » Physics

Studies in Fuzziness and Soft Computing #13: Incomplete Information: Rough Set Analysis New Trade Paper
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