ISBN: 9783030407933 - feature learning and understanding: algorithms and applications (information fusion and data science) (17 Ergebnisse)

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Gebunden. Zustand: New. Offers advanced feature learning methods, such as sparse learning, and deep-learning-based feature learning&nbspIncludes also traditional and cutting-edge feature learning methodsContains the detailed theoretical analysis of each featu.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book covers the essential concepts and strategies within traditional and cutting-edge feature learning methods thru both theoretical analysis and case studies. Good features give good models and it is usually not classifiers but features that determine the effectiveness of a model. In this book, readers can find not only traditional feature learning methods, such as principal component analysis, linear discriminant analysis, and geometrical-structure-based methods, but also advanced feature learning methods, such as sparse learning, low-rank decomposition, tensor-based feature extraction, and deep-learning-based feature learning. Each feature learning method has its own dedicated chapter that explains how it is theoretically derived and shows how it is implemented for real-world applications. Detailed illustrated figures are included for better understanding. This book can be used by students, researchers, and engineers looking for a reference guide for popular methods of feature learning and machine intelligence.…

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Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book covers the essential concepts and strategies within traditional and cutting-edge feature learning methods thru both theoretical analysis and case studies. Good features give good models and it is usually not classifiers but features that determine the effectiveness of a model. In this book, readers can find not only traditional feature learning methods, such as principal component analysis, linear discriminant analysis, and geometrical-structure-based methods, but also advanced feature learning methods, such as sparse learning, low-rank decomposition, tensor-based feature extraction, and deep-learning-based feature learning. Each feature learning method has its own dedicated chapter that explains how it is theoretically derived and shows how it is implemented for real-world applications. Detailed illustrated figures are included for better understanding. This book can be used by students, researchers, and engineers looking for a reference guide for popular methods of feature learning and machine intelligence. 308 pp. Englisch.…

Hardcover. Zustand: Brand New. 305 pages. 9.25x6.10x9.21 inches. In Stock. This item is printed on demand.

Buch. Zustand: Neu. Feature Learning and Understanding | Algorithms and Applications | Haitao Zhao (u. a.) | Buch | Information Fusion and Data Science | xiv | Englisch | 2020 | Springer | EAN 9783030407933 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.…

Buch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book covers the essential concepts and strategies within traditional and cutting-edge feature learning methods thru both theoretical analysis and case studies. Good features give good models and it is usually not classifiers but features that determine the effectiveness of a model. In this book, readers can find not only traditional feature learning methods, such as principal component analysis, linear discriminant analysis, and geometrical-structure-based methods, but also advanced feature learning methods, such as sparse learning, low-rank decomposition, tensor-based feature extraction, and deep-learning-based feature learning. Each feature learning method has its own dedicated chapter that explains how it is theoretically derived and shows how it is implemented for real-world applications. Detailed illustrated figures are included for better understanding. This book can be used by students, researchers, and engineers looking for a reference guide for popular methods of feature learning and machine intelligence.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 308 pp. Englisch.…

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