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portada Feature Learning and Understanding: Algorithms and Applications
Type
Physical Book
Author
Publisher
Language
English
Pages
291
Format
Paperback
Dimensions
23.4 x 15.6 x 1.7 cm
Weight
0.44 kg.
ISBN13
9783030407964
Categories

Feature Learning and Understanding: Algorithms and Applications

Haitao Zhao (Author) · Henry Leung (Author) · Zhihui Lai (Author) · Springer · Paperback

Feature Learning and Understanding: Algorithms and Applications - Zhao, Haitao ; Lai, Zhihui ; Leung, Henry

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Synopsis "Feature Learning and Understanding: Algorithms and Applications"

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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