Fr. 198.00

Machine Learning Paradigms: Theory and Application

Inglese · Copertina rigida

Spedizione di solito entro 2 a 3 settimane (il titolo viene stampato sull'ordine)

Descrizione

Ulteriori informazioni

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.

Sommario

Part I: Machine Learning in  Feature Selection.- Hybrid Feature Selection Method Based On The Genetic Algorithm And Pearson Correlation Coe cient.- Weighting Attributes and Decision Rules through Rankings and Discretisation Parameters.- Greedy Selection of Attributes to be Discretised.- Part II: Machine Learning in Classification and Ontology.- Machine learning for Enhancement Land Cover and Crop Types Classification.

Info autore



Riassunto

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.

Dettagli sul prodotto

Con la collaborazione di Abou Ella Hassanien (Editore), Aboul Ella Hassanien (Editore), Aboul Ella Hassanien (Editore)
Editore Springer, Berlin
 
Lingue Inglese
Formato Copertina rigida
Pubblicazione 01.01.2018
 
EAN 9783030023560
ISBN 978-3-0-3002356-0
Pagine 474
Dimensioni 158 mm x 40 mm x 242 mm
Peso 874 g
Illustrazioni IX, 474 p. 242 illus., 152 illus. in color.
Serie Studies in Computational Intelligence
Studies in Computational Intelligence
Categoria Scienze naturali, medicina, informatica, tecnica > Tecnica > Tematiche generali, enciclopedie

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