A Compressive Classification Framework for High-Dimensional Data
We propose a compressive classification framework for settings where the data dimensionality is significantly larger than the sample size. The proposed method, referred to as compressive regularized discriminant analysis (CRDA), is based on linear discriminant analysis and has the ability to select...
Main Authors: | Muhammad Naveed Tabassum, Esa Ollila |
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Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
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Series: | IEEE Open Journal of Signal Processing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9258370/ |
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