Granular Computing in Decision Approximation
An Application of Rough Mereology
Authors: Polkowski, Lech, Artiemjew, Piotr
Free Preview- Recent research on Granular Computing in Decision Approximation
- Fully develops the topic of granular computing in classifier synthesis
- Presents applied algorithms which are illustrated with simple hand examples
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- About this book
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This book presents a study in knowledge discovery in data with knowledge understood as a set of relations among objects and their properties. Relations in this case are implicative decision rules and the paradigm in which they are induced is that of computing with granules defined by rough inclusions, the latter introduced and studied within rough mereology, the fuzzified version of mereology. In this book basic classes of rough inclusions are defined and based on them methods for inducing granular structures from data are highlighted. The resulting granular structures are subjected to classifying algorithms, notably k—nearest neighbors and bayesian classifiers.
Experimental results are given in detail both in tabular and visualized form for fourteen data sets from UCI data repository. A striking feature of granular classifiers obtained by this approach is that preserving the accuracy of them on original data, they reduce substantially the size of the granulated data set as well as the set of granular decision rules. This feature makes the presented approach attractive in cases where a small number of rules providing a high classification accuracy is desirable. As basic algorithms used throughout the text are explained and illustrated with hand examples, the book may also serve as a textbook.
- Reviews
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“The book provides an extended presentation of granular computing, focusing on applications in classification/decision theory. … the book is intended to students and researchers interested in granular computing.” (Florin Gorunescu, zbMATH 1314.68006, 2015)
- Table of contents (11 chapters)
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Similarity and Granulation
Pages 1-15
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Mereology and Rough Mereology: Rough Mereological Granulation
Pages 17-31
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Learning Data Classification: Classifiers in General and in Decision Systems
Pages 33-62
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Methodologies for Granular Reflections
Pages 63-104
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Covering Strategies
Pages 105-220
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Table of contents (11 chapters)
- Download Preface 1 PDF (80.9 KB)
- Download Sample pages 2 PDF (166 KB)
- Download Table of contents PDF (164.4 KB)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Granular Computing in Decision Approximation
- Book Subtitle
- An Application of Rough Mereology
- Authors
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- Lech Polkowski
- Piotr Artiemjew
- Series Title
- Intelligent Systems Reference Library
- Series Volume
- 77
- Copyright
- 2015
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing Switzerland
- eBook ISBN
- 978-3-319-12880-1
- DOI
- 10.1007/978-3-319-12880-1
- Hardcover ISBN
- 978-3-319-12879-5
- Softcover ISBN
- 978-3-319-36621-0
- Series ISSN
- 1868-4394
- Edition Number
- 1
- Number of Pages
- XV, 452
- Number of Illustrations
- 230 b/w illustrations
- Topics
