• Anglický jazyk

Feature Learning and Understanding

Autor: Haitao Zhao

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... Viac o knihe

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138.59 €

bežná cena: 153.99 €

O knihe

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.

  • Vydavateľstvo: Springer International Publishing
  • Rok vydania: 2021
  • Formát: Paperback
  • Rozmer: 235 x 155 mm
  • Jazyk: Anglický jazyk
  • ISBN: 9783030407964

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