© 2019

Machine Learning Paradigms: Theory and Application

  • Aboul Ella Hassanien
  • Presents machine learning paradigms

  • Focuses on recent theory and applications

  • Written by experts in the field


Part of the Studies in Computational Intelligence book series (SCI, volume 801)

Table of contents

  1. Front Matter
    Pages i-ix
  2. Machine Learning in Feature Selection

  3. Machine Learning in Classification and Ontology

    1. Front Matter
      Pages 69-69
    2. Noureldin Laban, Bassam Abdellatif, Hala M. Ebeid, Howida A. Shedeed, Mohamed F. Tolba
      Pages 71-87
    3. Barry Fitzgerald, Conor Ryan, Joe Sullivan
      Pages 89-110
    4. Djamel Saba, Fatima Zohra Laallam, Houssem Eddine Degha, Brahim Berbaoui, Rachid Maouedj
      Pages 135-167
    5. Doaa Mohey El-Din, Mohamed Hamed N. Taha, Nour Eldeen M. Khalifa
      Pages 189-210
    6. Meryem Talha, Siham Boulaknadel, Driss Aboutajdine
      Pages 211-232
    7. Randa Benkhelifa, Nasria Bouhyaoui, Fatima Zohra Laallam
      Pages 233-251
    8. Ali Ahmed, Abdelhameed Ibrahim, Sherif Hussein
      Pages 253-270
  4. Bio-inspiring Optimization and Applications

    1. Front Matter
      Pages 287-287
    2. Marwa Gamal, Rawya Rizk, Hani Mahdi, Basem Elhady
      Pages 289-308
    3. Gehad Ismail Sayed, Mona Soliman, Aboul Ella Hassanien
      Pages 309-326

About this book


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.


Computational Intelligence Machine Learning Foundations of Machine Learning Pattern Recognition Social Networks

Editors and affiliations

  • Aboul Ella Hassanien
    • 1
  1. 1.Faculty of Computers and InformationCairo UniversityGizaEgypt

About the editors

Bibliographic information

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