• Generalized Principal Component Analysis

Generalized Principal Component Analysis

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Est. Date: Nov 7, 2025

The main goal of this book is to introduce a new method to study hybrid models, referred to as generalized principal component analysis. The general problems that GPCA aims to address represents a fairly general class of unsupervised learning problems— many data clustering and modeling methods in machine learning can be viewed as special cases of this method. This book provides a comprehensive introduction of the fundamental statistical, geometric and algebraic concepts associated with the estimation (and segmentation) of the hybrid models, especially the hybrid linear models.

  • Author(s): Yi Ma, Shankar Sastry, Rene Vidal
  • Publisher: Springer New York
  • Language: en
  • Pages: 300
  • Binding: Hardcover
  • Edition: 1st ed. 2016
  • Published: 2015-12-06
  • Dimensions: Height: 9 Inches, Length: 6.25 Inches, Weight: 22.41219355492 Pounds, Width: 1.5 Inches
  • Estimated Delivery: Nov 7, 2025
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