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Interval-valued methods in classifications and decisions

Author: Urszula Bentkowska
Publisher: Cham : Springer, 2019. ©2020
Series: Studies in fuzziness and soft computing, v. 378.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: (OCoLC)1082233192
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Urszula Bentkowska
ISBN: 9783030129279 3030129276
OCLC Number: 1111295360
Notes: Fuzzy Sets and their Extensions.- Aggregation in Interval-valued Settings.- Decision Making using Interval-valued Aggregation.- Optimization Problem of k-NN classifier in DNA Microarray Methods.- Interval-valued Methods in Medical Decision Support Systems.
Description: 1 online resource (163 pages).
Contents: Fuzzy Sets and their Extensions --
Aggregation in Interval-valued Settings --
Decision Making using Interval-valued Aggregation --
Optimization Problem of k-NN classifier in DNA Microarray Methods --
Interval-valued Methods in Medical Decision Support Systems.
Series Title: Studies in fuzziness and soft computing, v. 378.
Responsibility: Urszula Bentkowska.

Abstract:

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.

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