Interval-Valued Methods in Classifications and Decisions

  • Urszula Bentkowska

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 378)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Foundations

    1. Front Matter
      Pages 1-1
    2. Urszula Bentkowska
      Pages 3-23
    3. Urszula Bentkowska
      Pages 25-68
  3. Applications

    1. Front Matter
      Pages 69-69
    2. Urszula Bentkowska
      Pages 71-82
    3. Urszula Bentkowska
      Pages 131-133
    4. Urszula Bentkowska
      Pages 135-158
  4. Back Matter
    Pages 159-163

About this book


This book describes novel algorithms based on interval-valued fuzzy methods that are expected to improve classification and decision-making processes under incomplete or imprecise information. At first, it introduces interval-valued fuzzy sets. It then discusses new methods for aggregation on interval-valued settings, and the most common properties of interval-valued aggregation operators. It then presents applications such as decision making using interval-valued aggregation, and classification in case of missing values. Interesting applications of the developed algorithms to DNA microarray analysis and in medical decision support systems are shown. The book is intended not only as a timely report for the community working on fuzzy sets and their extensions but also for researchers and practitioners dealing with the problems of uncertain or imperfect information.



Interval-valued Aggregations Fuzzy Preference Relations Classification in the Case of Missing Values Vertical Decomposition Interval Modeling of Incomplete Data Classification of Microarray Data

Authors and affiliations

  • Urszula Bentkowska
    • 1
  1. 1.Faculty of Mathematics and Natural SciencesUniversity of RzeszówRzeszówPoland

Bibliographic information