How fuzzy concepts contribute to machine learning

by Eftekhari, Mahdi

Type Book

Rate 0.0 /5

Details

Files

Reviews

Download

Title Statements

Full title :How fuzzy concepts contribute to machine learning / Mahdi Eftekhari, Adel Mehrpooya, Farid Saberi-Movahed, Vicenç Torra.

Summary

This book introduces some contemporary approaches on the application of fuzzy and hesitant fuzzy sets in machine learning tasks such as classification, clustering and dimension reduction. Many situations arise in machine learning algorithms in which applying methods for uncertainty modeling and multi-criteria decision making can lead to a better understanding of algorithms behavior as well as achieving good performances. Specifically, the present book is a collection of novel viewpoints on how fuzzy and hesitant fuzzy concepts can be applied to data uncertainty modeling as well as being used to solve multi-criteria decision making challenges raised in machine learning problems. Using the multi-criteria decision making framework, the book shows how different algorithms, rather than human experts, are employed to determine membership degrees. The book is expected to bring closer the communities of pure mathematicians of fuzzy sets and data scientists. .

Edition Statements

Publication Date:©2022

Publication Statements

Publisher(s):Springer
Place of Publication:Cham
Language:eng
Publication Date:©2022

The Physical Object

Description:1 online resource : : color illustrations.

Edition Identifiers

ISBN:9783030940669, 3030940667
DOI:10.1007/978-3-030-94066-9
oclc:on1298165351
LC Classification:Q325.5
Dewey Decimal:006.3/1015113223

Chapter 1: Preliminaries -- Chapter 2: A Denition for Hesitant Fuzzy Partitions -- Chapter 3: Unsupervised Feature Selection Method. Chapter 4: Fuzzy Partitioning of Continuous Attributes -- Chapter 5: Comparing Different Stopping Criteria.