Regularized Discriminant Analysis: A Large Dimensional Study

Regularized Discriminant Analysis: A Large Dimensional Study

In this thesis, we focus on studying the performance of general regularized discriminant analysis (RDA) classifiers. The data used for analysis is assumed to follow Gaussian mixture model with different means and covariances. RDA offers a rich class of regularization options, covering as special cas...

Full description

Bibliographic Details
Main Author: Yang, Xiaoke
Other Authors: Al-Naffouri, Tareq Y.
Language:en
Published: 2018
Subjects:
Random matrix theory
Machine Learning
discriminant Analysis
Online Access:http://hdl.handle.net/10754/627734

Internet

http://hdl.handle.net/10754/627734

Similar Items