Evaluating Sparse Feature Selection Methods: A Theoretical and Empirical Perspective

This paper analyzes two main categories of feature selection: filter methods (such as minimum redundancy maximum relevance, CHI2, Kruskal–Wallis, and ANOVA) and embedded methods (such as alternating direction method of multipliers (BP_ADMM), least absolute shrinkage and selection operator, and ortho...

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Bibliographic Details
Main Authors: Monica Fira, Liviu Goras, Hariton-Nicolae Costin
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/15/7/3752
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