10% off all books and free delivery over £40 - Last Express Posting Date for Christmas: 20th December
Buy from our bookstore and 25% of the cover price will be given to a school of your choice to buy more books. *15% of eBooks.

How Fuzzy Concepts Contribute to Machine Learning

View All Editions

The selected edition of this book is not available to buy right now.
Add To Wishlist
Write A Review

About

How Fuzzy Concepts Contribute to Machine Learning Synopsis

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. 

About This Edition

ISBN: 9783030940683
Publication date: 17th February 2023
Author: Mahdi Eftekhari, Adel Mehrpooya, Farid SaberiMovahed, Vicenç Torra
Publisher: Springer Nature Switzerland AG
Format: Paperback
Pagination: 167 pages
Series: Studies in Fuzziness and Soft Computing
Genres: Artificial intelligence
Databases