Main Machine Learning Paradigms: Theory and Application

Machine Learning Paradigms: Theory and Application

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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.
Request Code : ZLIBIO3196432
Categories:
Volume:
801
Year:
2018
Edition:
1
Publisher:
Springer
Language:
English
Pages:
474
ISBN 10:
2018944351
ISBN 13:
9783030023560
ISBN:
9783030023577,9783030023560,2018944351
Series:
Studies in Computational Intelligence
This book is not available due to the complaint of the copyright holder.

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