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Soft regression trees: A model variant and a decomposition training algorithm
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DOI：10.1016/j.ejor.2025.08.050.png)
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Abstract
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• A new soft regression trees variant with the conditional computation property is proposed. • A universal approximation result is provided for such soft regression trees. • A convergent training decomposition general scheme is presented. • A convergent version with initialization and reassignment heuristics is developed. • Our algorithm outperforms state-of-the-art deterministic/soft regression tree methods.
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6
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2.2W
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6.4W
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