Название: Fusion of Machine Learning Paradigms: Theory and ApplicationsАвтор: Ioannis K. Hatzilygeroudis, George A. Tsihrintzis, Lakhmi C. Jain
Издательство: Springer
Год: 2023
Страниц: 204
Язык: английский
Формат: pdf (true), epub
Размер: 28.3 MB
This book aims at updating the relevant computer science-related research communities, including professors, researchers, scientists, engineers and students, as well as the general reader from other disciplines, on the most recent advances in applications of methods based on Fusing Machine Learning Paradigms. Integrated or Hybrid Machine Learning methodologies combine together two or more Machine Learning approaches achieving higher performance and better efficiency when compared to those of their constituent components and promising major impact in science, technology and the society. The book consists of an editorial note and an additional eight chapters and is organized into two parts, namely: (i) Recent Application Areas of Fusion of Machine Learning Paradigms and (ii) Applications that can clearly benefit from Fusion of Machine Learning Paradigms. One of the most successful and most promising Machine Learning approaches that, in recent years, have claimed a large part of research activities is that of Integrated or Hybrid Approaches and Methodologies.
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