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Average weight margin-based feature selection with three-way decision
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DOI：10.1016/j.patcog.2025.113009.png)
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Abstract
En 中文
• A weighted neighborhood rough set model is constructed by considering the importance of different samples and features. • A sample weight function and a margin-based gradient optimization algorithm are developed to learn the weights of samples and features. • A forward-adding feature selection algorithm based on the average weight margin measure is proposed to generate an optimal feature subset with a large margin.
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