Machine Learning Paradigms: Theory and Application (Studies in Computational Intelligence Book 801)
Category
Author
Publication
Springer
0 View
'
From the Back Cover
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 todays 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. --This text refers to the hardcover edition.
About the Author
--This text refers to the hardcover edition.
Similar Books
Other Authors' Books
Other Publishing Books
User Reviews
Rating
average 0