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Machine learning paradigms = theory ...

Hassanien, Aboul Ella.

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Machine learning paradigms = theory and application /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Machine learning paradigms/ edited by Aboul Ella Hassanien.
其他題名:	theory and application /
其他作者:	Hassanien, Aboul Ella.
出版者:	Cham :Springer International Publishing : : 2019.,
面頁冊數:	ix, 474 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Machine learning. -
電子資源:	https://doi.org/10.1007/978-3-030-02357-7
ISBN:	9783030023577

Machine learning paradigms = theory and application /
Machine learning paradigmstheory and application /[electronic resource] :edited by Aboul Ella Hassanien. - Cham :Springer International Publishing :2019. - ix, 474 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.8011860-949X ;. - Studies in computational intelligence ;v.801..

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.

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.

ISBN: 9783030023577

Standard No.: 10.1007/978-3-030-02357-7doiSubjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5 / .M334 2019

Dewey Class. No.: 006.31

Machine learning paradigms = theory and application /
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520 $a 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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