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Inhibitory Rules in Data Analysis

A Rough Set Approach

  • Authors
  • Pawel Delimata
  • Mikhail Ju. Moshkov
  • Andrzej Skowron
  • Zbigniew Suraj

Part of the Studies in Computational Intelligence book series (SCI, volume 163)

Table of contents

  1. Front Matter
  2. Pawel Delimata, Mikhail Ju. Moshkov, Andrzej Skowron, Zbigniew Suraj
    Pages 1-8
  3. Pawel Delimata, Mikhail Ju. Moshkov, Andrzej Skowron, Zbigniew Suraj
    Pages 9-29
  4. Pawel Delimata, Mikhail Ju. Moshkov, Andrzej Skowron, Zbigniew Suraj
    Pages 31-41
  5. Pawel Delimata, Mikhail Ju. Moshkov, Andrzej Skowron, Zbigniew Suraj
    Pages 43-62
  6. Pawel Delimata, Mikhail Ju. Moshkov, Andrzej Skowron, Zbigniew Suraj
    Pages 63-79
  7. Pawel Delimata, Mikhail Ju. Moshkov, Andrzej Skowron, Zbigniew Suraj
    Pages 81-86
  8. Pawel Delimata, Mikhail Ju. Moshkov, Andrzej Skowron, Zbigniew Suraj
    Pages 87-97
  9. Pawel Delimata, Mikhail Ju. Moshkov, Andrzej Skowron, Zbigniew Suraj
    Pages 99-106
  10. Pawel Delimata, Mikhail Ju. Moshkov, Andrzej Skowron, Zbigniew Suraj
    Pages 107-108
  11. Back Matter

About this book

Introduction

This monograph is devoted to theoretical and experimental study of inhibitory decision and association rules. Inhibitory rules contain on the right-hand side a relation of the kind "attribut does not equal value". The use of inhibitory rules instead of deterministic (standard) ones allows us to describe more completely information encoded in decision or information systems and to design classifiers of high quality.

The most important feature of this monograph is that it includes an advanced mathematical analysis of problems on inhibitory rules. We consider algorithms for construction of inhibitory rules, bounds on minimal complexity of inhibitory rules, and algorithms for construction of the set of all minimal inhibitory rules.We also discuss results of experiments with standard and lazy classifiers based on inhibitory rules. These results show that inhibitory decision and association rules can be used in data mining and knowledge discovery both for knowledge representation and for prediction. Inhibitory rules can be also used under the analysis and design of concurrent systems.

The results obtained in the monograph can be useful for researchers in such areas as machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, test theory, and logical analysis of data (LAD). The monograph can be used under the creation of courses for graduate students and for Ph.D. studies.

Keywords

Computational Intelligence Data Analysis Extension Inhibitory Rules Rough Sets algorithm algorithms calculus classification information system

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-85638-2
  • Copyright Information Springer-Verlag Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-85637-5
  • Online ISBN 978-3-540-85638-2
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site
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