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Machine Learning Paradigms: Theory and Application: Studies in Computational Intelligence, cartea 801

Editat de Aboul Ella Hassanien
en Limba Engleză Hardback – 21 dec 2018
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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Specificații

ISBN-13: 9783030023560
ISBN-10: 3030023567
Pagini: 630
Ilustrații: IX, 474 p. 242 illus., 152 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.85 kg
Ediția:1st ed. 2019
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Cham, Switzerland

Cuprins

Part I: Machine Learning in  Feature Selection.- Hybrid Feature Selection Method Based On The Genetic Algorithm And Pearson Correlation Coefficient.- 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.

Notă biografică



Textul de pe ultima copertă

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.

Caracteristici

Presents machine learning paradigms Focuses on recent theory and applications Written by experts in the field