Machine Learning Paradigms: Theory and Application (Hardcover, 1st ed. 2019)

The book focuses on machine learning. Divided into three parts, the first part discusses the feature selection problem. The second part then describes the application of machine learning in the classification problem, while the third part presents an overview of real-world applications of swarm-based optimization algorithms. The concept of machine learning (ML) is not new in the field of computing. However, due to the ever-changing nature of requirements in today's world it has emerged in the form of completely new avatars. Now everyone is talking about ML-based solution strategies for a given problem set. The book includes research articles and expository papers on the theory and algorithms of machine learning and bio-inspiring optimization, as well as papers on numerical experiments and real-world applications.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Studies in Computational Intelligence, 801
Release date:	2019
First published:	2019
Editors:	Aboul Ella Hassanien
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	474
Edition:	1st ed. 2019
ISBN-13:	978-3-03-002356-0
Categories:	Books > Computing & IT > Applications of computing > Pattern recognition Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	3-03-002356-7
Barcode:	9783030023560

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