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Feature Selection Under Orthogonal Regression With Redundancy Minimizing

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IEEE ICASSP 2020 Virtual Conference May 2020

Various supervised embedded methods have been proposed to select discriminative features from original ones, such as Feature Selection with Orthogonal Regression (FSOR) and Robust Feature Selection. Compared with embedded methods based on the least square

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Feature Selection Under Orthogonal Regression With Redundancy Minimizing

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Various supervised embedded methods have been proposed to select discriminative features from original ones, such as Feature Selection with Orthogonal Regression (FSOR) and Robust Feature Selection. Compared with embedded methods based on the least square