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Granular Computing in Decision Approximation

An Application of Rough Mereology

  • Lech Polkowski
  • Piotr Artiemjew

Part of the Intelligent Systems Reference Library book series (ISRL, volume 77)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Lech Polkowski, Piotr Artiemjew
    Pages 1-15
  3. Lech Polkowski, Piotr Artiemjew
    Pages 17-31
  4. Lech Polkowski, Piotr Artiemjew
    Pages 63-104
  5. Lech Polkowski, Piotr Artiemjew
    Pages 105-220
  6. Lech Polkowski, Piotr Artiemjew
    Pages 221-276
  7. Lech Polkowski, Piotr Artiemjew
    Pages 303-348
  8. Lech Polkowski, Piotr Artiemjew
    Pages 349-398
  9. Lech Polkowski, Piotr Artiemjew
    Pages 399-415
  10. Lech Polkowski, Piotr Artiemjew
    Pages 417-422
  11. Back Matter
    Pages 423-452

About this book

Introduction

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.

Keywords

Computational Intelligence Decision Approximation Granular Computing Intelligent Systems Rough Mereology

Authors and affiliations

  • Lech Polkowski
    • 1
  • Piotr Artiemjew
    • 2
  1. 1.Department of Mathematics and Computer Science, University of Warmia and MazuryDepartment of Computer Science, Polish-Japanese Institute of Information Technology, Warsaw, Poland, andOlsztynPoland
  2. 2.Department of Mathematics and Computer ScienceUniversity of Warmia and MazuryOlsztynPoland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-12880-1
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-12879-5
  • Online ISBN 978-3-319-12880-1
  • Series Print ISSN 1868-4394
  • Series Online ISSN 1868-4408
  • Buy this book on publisher's site
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