Téléchargez le livre : Feature Learning and Understanding

Feature Learning and Understanding

Algorithms and Applications de

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Éditeur :

Springer


Collection :

Information Fusion and Data Science

Paru le : 2020-04-03

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Description

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.
Pages
291 pages
Collection
Information Fusion and Data Science
Parution
2020-04-03
Marque
Springer
EAN papier
9783030407933
EAN PDF
9783030407940
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
29
Taille du fichier
10271 Ko
Prix
137,14 €
EAN EPUB
9783030407940
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
29
Taille du fichier
36669 Ko
Prix
137,14 €

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