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feature selection

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Researchers Propose Feature Selection to Improve Neural Additive Model Efficiency and Interpretability Technology
Artificial Intelligence #machine learning#neural networks

Researchers Propose Feature Selection to Improve Neural Additive Model Efficiency and Interpretability

A research paper proposes adding feature selection mechanisms to Neural Additive Models (NAM) and Neural Basis Models (NBM) to reduce computational costs and enable handling of feature interactions in high-dimensional datasets. The method updates selection weights during training, achieving better or comparable performance to state-of-the-art GAMs.

Jul 8, 2026 1 source