Comparison of robust discriminant methods.

<div><p>This paper presents an improved robust Fisher discriminant method designed to handle high-dimensional data, particularly in the presence of outliers. Traditional Fisher discriminant methods are sensitive to outliers, which can significantly degrade their performance. To address t...

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Bibliographic Details
Main Author:	Shaojuan Ma (12750125) (author)
Other Authors:	Yubing Duan (21533553) (author)
Published:	2025
Subjects:	Genetics Molecular Biology Neuroscience Evolutionary Biology Inorganic Chemistry Infectious Diseases Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified robust statistical analysis improved robust algorithms fisher discriminant outperforms fisher discriminant model fisher discriminant framework conduct comparative experiments robust discriminant methods dimensional data analysis dimensional data data contaminated xlink "> variables exceeds valuable contribution study provides significantly degrade results demonstrate reliable choice practical solution paper presents handling complex covariance matrix computational stability
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Comparison of robust discriminant methods.

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