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A. Ayesh

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Open access Aug 2026

RMAM: A Rule-based Filter Method with Modified Huffman Ranking for Variable Selection in Supervised Learning

RMAM integrates a new Modified Huffman Ranker (MHR) that computes an adaptive cut-off threshold to distinguish essential from redundant variables and demonstrates RMAM’s effectiveness as a practical variable selection approach for supervised learning applications.

Talib Alshehhi, Ying-Jie Yang, Feng Chen et al. · 0 citations

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