Metaheuristics for Machine Learning: New Advances and Tools

Metaheuristics have been successfully integrated into machine learning techniques, improving their performance in supervised and unsupervised problems. This book explores how metaheuristics can be adapted to enhance machine learning tools and provides real-world applications in clustering, big data, machine health monitoring, underwater sonar targets, and banking.

Format: Hardback
Length: 223 pages
Publication date: 14 March 2023
Publisher: Springer Verlag, Singapore

The integration of metaheuristics with machine learning techniques has gained significant attention in recent years, resulting in remarkable successes across supervised and unsupervised problem domains. Metaheuristics, which involve the use of intelligent search strategies to solve complex problems, have proven to be powerful tools for optimizing machine learning algorithms. One of the most exciting developments in this field is the automatic generation of programs through metaheuristics, known as evolutionary computation and swarm intelligence. This approach has gained widespread popularity due to its ability to generate optimized solutions efficiently and effectively.

This book delves into various approaches for integrating metaheuristics into machine learning techniques, offering a comprehensive theoretical and practical understanding. It explores how metaheuristics can be tailored to enhance machine learning tools and provides an overview of the primary metaheuristic programming methods. Furthermore, real-world applications are presented to illustrate the practical implications of metaheuristics, including clustering, big data analysis, machine health monitoring, underwater sonar target detection, and banking.

By leveraging the strengths of metaheuristics, machine learning algorithms can be improved, leading to more accurate predictions, efficient optimization, and better decision-making processes. This book serves as a valuable resource for researchers, practitioners, and students interested in advancing the field of machine learning and applying metaheuristics to solve complex real-world problems.

Weight: 530g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811938870
Edition number: 1st ed. 2023