Fusion machine learning paradigms (35 Ergebnisse)
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Hardcover. Zustand: new. Hardcover. 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 Lea…rning 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. This book is directed toward professors, researchers, scientists, engineers and students in Machine Learning-related disciplines, as the hybridism presented, and the case studies described provide researchers with successful approaches and initiatives to efficiently address complex classification or regression problems. It is also directed toward readers who come from other disciplines, including Engineering, Medicine or Education Sciences, and are interested in becoming versed in some of the most recent Machine Learning-based technologies. Extensive lists of bibliographic references at the end of each chapter guide the readers to probe further into the application areas of interest to them. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Fusion of Machine Learning Paradigms : Theory and Applications
Hatzilygeroudis, Ioannis K. (EDT); Tsihrintzis, George A. (EDT); Jain, Lakhmi C. (EDT)
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Fusion of Machine Learning Paradigms : Theory and Applications
Hatzilygeroudis, Ioannis K. (EDT); Tsihrintzis, George A. (EDT); Jain, Lakhmi C. (EDT)
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Fusion of Machine Learning Paradigms : Theory and Applications
Hatzilygeroudis, Ioannis K. (EDT); Tsihrintzis, George A. (EDT); Jain, Lakhmi C. (EDT)
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Fusion of Machine Learning Paradigms : Theory and Applications
Hatzilygeroudis, Ioannis K. (EDT); Tsihrintzis, George A. (EDT); Jain, Lakhmi C. (EDT)
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Taschenbuch. Zustand: Neu. Fusion of Machine Learning Paradigms | Theory and Applications | Ioannis K. Hatzilygeroudis (u. a.) | Taschenbuch | xii | Englisch | 2024 | Springer | EAN 9783031223730 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]c…om | Anbieter: preigu.
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Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | 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. This book is directed toward professors, researchers, scientists, engineers and students in Machine Learning-related disciplines, as the hybridism presented, and the case studies described provide researchers with successful approaches and initiatives to efficiently address complex classification or regression problems. It is also directed toward readers who come from other disciplines, including Engineering, Medicine or Education Sciences, and are interested in becoming versed in some of the most recent Machine Learning-based technologies. Extensive lists of bibliographic references at the end of each chapter guide the readers to probe further into the application areas of interest to them.
Fusion of Machine Learning Paradigms: Theory and Applications
Hatzilygeroudis, Ioannis K. (Editor)/ Tsihrintzis, George A. (Editor)/ Jain, Lakhmi C. (Editor)
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Sprache: Englisch
Verlag: Springer, Berlin|Springer International Publishing|Springer, 2023
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Verlag: Springer, Berlin|Springer International Publishing|Springer, 2024
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Buch. Zustand: Neu. Fusion of Machine Learning Paradigms | Theory and Applications | Ioannis K. Hatzilygeroudis (u. a.) | Buch | xii | Englisch | 2023 | Springer | EAN 9783031223709 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter:… preigu Print on Demand.
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 advance…s 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.This book is directed toward professors, researchers, scientists, engineers and students in Machine Learning-related disciplines, as the hybridism presented, and the case studies described provide researchers with successful approaches and initiatives to efficiently address complex classification or regression problems.It is also directed toward readers who come from other disciplines, including Engineering, Medicine or Education Sciences, and are interested in becoming versed in some of the most recent Machine Learning-based technologies. Extensive lists of bibliographic references at the end of each chapter guide the readers to probe further into the application areas of interest to them.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 212 pp. Englisch.
