Interval-valued methods in classifications and decisions /

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Bibliographic Details
Author / Creator:Bentkowska, Urszula, author.
Imprint:Cham : Springer, [2020]
©2020
Description:1 online resource (163 pages).
Language:English
Series:Studies in fuzziness and soft computing ; volume 378
Studies in fuzziness and soft computing ; v. 378.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/12601714
Hidden Bibliographic Details
ISBN:9783030129279
3030129276
9783030129262
3030129268
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.
Includes bibliographical references and index.
Print version record.
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 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.
Other form:Print version: Bentkowska, Urszula. Interval-valued methods in classifications and decisions. Cham : Springer, 2019 3030129268 9783030129262
Standard no.:10.1007/978-3-030-12