Interval-Valued Methods in Classifications and Decisions

✍ Scribed by Urszula Bentkowska

• Publisher: Springer International Publishing
• Year: 2020
• Tongue: English
• Leaves: 172
• Series: Studies in Fuzziness and Soft Computing 378
• Edition: 1st ed.
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter ....Pages i-xv
Front Matter ....Pages 1-1
Fuzzy Sets and Their Extensions (Urszula Bentkowska)....Pages 3-23
Aggregation in Interval-Valued Settings (Urszula Bentkowska)....Pages 25-68
Front Matter ....Pages 69-69
Decision Making Using Interval-Valued Aggregation (Urszula Bentkowska)....Pages 71-82
Optimization Problem of k-NN Classifier for Missing Values Case (Urszula Bentkowska)....Pages 83-105
Optimization Problem of k-NN Classifier in DNA Microarray Methods (Urszula Bentkowska)....Pages 107-120
Interval-Valued Methods in Medical Decision Support Systems (Urszula Bentkowska)....Pages 121-130
Summary (Urszula Bentkowska)....Pages 131-133
Tables with the Results of Experiments (Urszula Bentkowska)....Pages 135-158
Back Matter ....Pages 159-163

✦ Subjects

Engineering; Computational Intelligence; Computational Biology/Bioinformatics; Microarrays