Machine Learning Paradigms: Theory and Application

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.

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Summary

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.

Product details

• Assisted by: Abou Ella Hassanien (Editor), Aboul Ella Hassanien (Editor), Aboul Ella Hassanien (Editor)
• Publisher: Springer, Berlin
• Content: Book
• Product form: Hardback
• Publication date: 01.01.2018
• Subject: Natural sciences, medicine, IT, technology > Technology > General, dictionaries
• EAN: 9783030023560
• ISBN: 978-3-0-3002356-0
• Pages: 474
• Illustrations: IX, 474 p. 242 illus., 152 illus. in color.
• Dimensions (packing): 15.8 x 4 x 24.2 cm
• Weight (packing): 874 g
• Series: Studies in Computational Intelligence > 801; Studies in Computational Intelligence
• Subjects: B, Artificial Intelligence, Mustererkennung, engineering, pattern recognition, Automated Pattern Recognition, Computational Intelligence, Pattern recognition systems