Skip to main content
  • Book
  • © 2009

Rough Set Theory: A True Landmark in Data Analysis

  • Reports recent research results in rough set research
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Computational Intelligence (SCI, volume 174)

Buy it now

Buying options

eBook USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

This is a preview of subscription content, log in via an institution to check for access.

Table of contents (11 chapters)

  1. Front Matter

  2. Theoretical Contributions to Rough Set Theory

    1. Front Matter

      Pages 1-1
    2. Categorical Innovations for Rough Sets

      • P. Eklund, M. A. Galán, J. Karlsson
      Pages 45-69
  3. Rough Set Data Mining Activities

    1. Front Matter

      Pages 135-135
    2. Rough Clustering with Partial Supervision

      • Rafael Falcón, Gwanggil Jeon, Rafael Bello, Jechang Jeong
      Pages 137-161
    3. A Generic Scheme for Generating Prediction Rules Using Rough Sets

      • Hameed Al-Qaheri, Aboul Ella Hassanien, Ajith Abraham
      Pages 163-186
    4. Rough Web Caching

      • Sarina Sulaiman, Siti Mariyam Shamsuddin, Ajith Abraham
      Pages 187-211
  4. Rough Hybrid Models to Classification and Attribute Reduction

    1. Front Matter

      Pages 233-233
    2. Rough Sets and Evolutionary Computation to Solve the Feature Selection Problem

      • Rafael Bello, Yudel Gómez, Yailé Caballero, Ann Nowe, Rafael Falcón
      Pages 235-260
    3. Nature Inspired Population-Based Heuristics for Rough Set Reduction

      • Hongbo Liu, Ajith Abraham, Yanheng Li
      Pages 261-278
  5. Back Matter

About this book

Along the years, rough set theory has earned a well-deserved reputation as a sound methodology for dealing with imperfect knowledge in a simple though mathematically sound way. This edited volume aims at continue stressing the benefits of applying rough sets in many real-life situations while still keeping an eye on topological aspects of the theory as well as strengthening its linkage with other soft computing paradigms. The volume comprises 11 chapters and is organized into three parts. Part 1 deals with theoretical contributions while Parts 2 and 3 focus on several real world data mining applications. Chapters authored by pioneers were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed. Academics, scientists as well as engineers working in the rough set, computational intelligence, soft computing and data mining research area will find the comprehensive coverage of this book invaluable.

Editors and Affiliations

  • Norwegian University of Science and Technology, Trondheim, Norway

    Ajith Abraham

  • School of Information Technology and Engineering (SITE), Central University of Las Villas, Villa Clara, Cuba

    Rafael Falcón

  • Department of Computer Science, Central University of LasVillas, Villa Clara, Cuba

    Rafael Bello

Bibliographic Information

Buy it now

Buying options

eBook USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access