Feature Learning and Understanding

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  • Feature Learning and Understanding Book Detail

  • Author : Haitao Zhao
  • Release Date : 2020-04-03
  • Publisher : Springer Nature
  • Genre : Science
  • Pages : 299
  • ISBN 13 : 3030407942
  • File Size : 79,79 MB

Feature Learning and Understanding by Haitao Zhao PDF Summary

Book 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.

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