Rough Sets in Knowledge Discovery 2, Lech Polkowski

Автор: James G. Shanahan
Название: Soft Computing for Knowledge Discovery
ISBN: 1461369479 ISBN-13(EAN): 9781461369479
Издательство: Springer
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Описание: Knowledge discovery is an area of computer science that attempts to uncover interesting and useful patterns in data that permit a computer to perform a task autonomously or assist a human in performing a task more efficiently.
Soft Computing for Knowledge Discovery provides a self-contained and systematic exposition of the key theory and algorithms that form the core of knowledge discovery from a soft computing perspective. It focuses on knowledge representation, machine learning, and the key methodologies that make up the fabric of soft computing - fuzzy set theory, fuzzy logic, evolutionary computing, and various theories of probability (e.g. na ve Bayes and Bayesian networks, Dempster-Shafer theory, mass assignment theory, and others). In addition to describing many state-of-the-art soft computing approaches to knowledge discovery, the author introduces Cartesian granule features and their corresponding learning algorithms as an intuitive approach to knowledge discovery. This new approach embraces the synergistic spirit of soft computing and exploits uncertainty in order to achieve tractability, transparency and generalization. Parallels are drawn between this approach and other well known approaches (such as naive Bayes and decision trees) leading to equivalences under certain conditions.
The approaches presented are further illustrated in a battery of both artificial and real-world problems. Knowledge discovery in real-world problems, such as object recognition in outdoor scenes, medical diagnosis and control, is described in detail. These case studies provide further examples of how to apply the presented concepts and algorithms to practical problems.
The author provides web page access to an online bibliography, datasets, source codes for several algorithms described in the book, and other information.
Soft Computing for Knowledge Discovery is for advanced undergraduates, professionals and researchers in computer science, engineering and business information systems who work or have an interest in the dynamic fields of knowledge discovery and soft computing.

Автор: O. Maimon; M. Last
Название: Knowledge Discovery and Data Mining
ISBN: 1441948422 ISBN-13(EAN): 9781441948427
Издательство: Springer
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Цена: 19559.00 р.
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Описание: This book presents a specific and unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network methodology. Data Mining (DM) is the science of modelling and generalizing common patterns from large sets of multi-type data. DM is a part of KDD, which is the overall process for Knowledge Discovery in Databases. The accessibility and abundance of information today makes this a topic of particular importance and need. The book has three main parts complemented by appendices as well as software and project data that are accessible from the book's web site (http: //www.eng.tau.ac.iV-maimonlifn-kdg ). Part I (Chapters 1-4) starts with the topic of KDD and DM in general and makes reference to other works in the field, especially those related to the information theoretic approach. The remainder of the book presents our work, starting with the IFN theory and algorithms. Part II (Chapters 5-6) discusses the methodology of application and includes case studies. Then in Part III (Chapters 7-9) a comparative study is presented, concluding with some advanced methods and open problems. The IFN, being a generic methodology, applies to a variety of fields, such as manufacturing, finance, health care, medicine, insurance, and human resources. The appendices expand on the relevant theoretical background and present descriptions of sample projects (including detailed results).

Автор: Edward Szczerbicki
Название: Intelligent Systems for Knowledge Management
ISBN: 3642260632 ISBN-13(EAN): 9783642260636
Издательство: Springer
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Цена: 23508.00 р.
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Описание: A key area of research in intelligent systems development is focused on knowledge and information management, which is regarded as the crucial issue in smart decision-making support. The chapters of this book are a representative sample of this research.

Автор: R?diger Klar; Otto Opitz
Название: Classification and Knowledge Organization
ISBN: 3540629815 ISBN-13(EAN): 9783540629818
Издательство: Springer
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Цена: 12157.00 р.
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Описание: Large collections of data and information necessitate adequate methods for their analysis. The book presents such methods, proposes and discusses recent approaches and implementations and describes a series of practical applications.

Автор: Wojciech P. Ziarko
Название: Rough Sets, Fuzzy Sets and Knowledge Discovery
ISBN: 3540198857 ISBN-13(EAN): 9783540198857
Издательство: Springer
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Цена: 12157.00 р.
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Описание: This volume of workshop papers has been divided into sections on knowledge discovery methodologies and applications, the theory of rough sets and its extensions, machine learning applications of rough sets, and reasoning from uncertain data using both fuzzy and rough set methods.

Автор: Peng Wen; Yuefeng Li; Lech Polkowski; Yiyu Y. Yao;
Название: Rough Sets and Knowledge Technology
ISBN: 3642029612 ISBN-13(EAN): 9783642029615
Издательство: Springer
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Цена: 16769.00 р.
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Описание: 4th International Conference RSKT 2009 Gold Coast Australia July 1416 2009 Proceedings. .

Автор: Saman K. Halgamuge; Lipo Wang
Название: Classification and Clustering for Knowledge Discovery
ISBN: 3642065422 ISBN-13(EAN): 9783642065422
Издательство: Springer
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Цена: 29209.00 р.
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Описание: This book covers recent advances in unsupervised and supervised data analysis methods in Computational Intelligence for knowledge discovery. If labeled data or data with known associations are available, we may be able to use supervised data analysis methods, such as classifying neural networks, fuzzy rule-based classifiers, and decision trees.

Автор: Evangelos Triantaphyllou
Название: Data Mining and Knowledge Discovery via Logic-Based Methods
ISBN: 1461426138 ISBN-13(EAN): 9781461426134
Издательство: Springer
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Цена: 23058.00 р.
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Описание: This book uses a novel method to study a series of interconnected key data mining and knowledge discovery problems in depth and in a way that stimulates the quest for more knowledge. It also presents a collection of examples, many from real-life applications.

Автор: Evangelos Triantaphyllou
Название: Data Mining and Knowledge Discovery via Logic-Based Methods
ISBN: 1441916296 ISBN-13(EAN): 9781441916297
Издательство: Springer
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Цена: 23058.00 р.
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Описание: This book uses a novel method to study a series of interconnected key data mining and knowledge discovery problems in depth and in a way that stimulates the quest for more knowledge. It also presents a collection of examples, many from real-life applications.

Автор: Didier Dubois; Henri Prade; Erich Peter Klement
Название: Fuzzy Sets, Logics and Reasoning about Knowledge
ISBN: 0792359771 ISBN-13(EAN): 9780792359777
Издательство: Springer
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Цена: 27944.00 р.
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Описание: Features results concerning the genuinely logical aspects of fuzzy sets in relation to algebraic considerations, knowledge representation and commonsense reasoning. This work offers a look at multiple-valued and fuzzy set-based logics, in an artificial intelligence perspective.

Автор: Didier Dubois; Henri Prade; Erich Peter Klement
Название: Fuzzy Sets, Logics and Reasoning about Knowledge
ISBN: 9048153247 ISBN-13(EAN): 9789048153244
Издательство: Springer
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Описание: Fuzzy Sets, Logics and Reasoning about Knowledge reports recent results concerning the genuinely logical aspects of fuzzy sets in relation to algebraic considerations, knowledge representation and commonsense reasoning.

Автор: Wolfgang A. Gaul; Dietmar Pfeifer
Название: From Data to Knowledge
ISBN: 3540603549 ISBN-13(EAN): 9783540603542
Издательство: Springer
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Цена: 18167.00 р.
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Описание: The subject of this work is the incorporation and integration of mathematical and statistical techniques, and information science topics into the field of classification, data analysis, and knowledge organization.