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Hinge Regression Tree offers novel Newton method for oblique regression tree splitting

Researchers have introduced the Hinge Regression Tree (HRT), a novel method for creating oblique regression trees. HRT reframes the split-finding process as a non-linear least-squares problem, enabling efficient optimization through a damped Newton method. The paper demonstrates that HRT's model class is a universal approximator and shows competitive performance against existing single-tree baselines on various benchmarks. AI

影响 Introduces a new algorithmic approach for oblique regression trees, potentially improving model interpretability and performance.

排序理由 This is a research paper detailing a new algorithmic approach for oblique regression trees.

在 arXiv cs.LG 阅读 →

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Hinge Regression Tree offers novel Newton method for oblique regression tree splitting

报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Hongyi Li, Han Lin, Jun Xu ·

    Hinge Regression Tree: A Newton Method for Oblique Regression Tree Splitting

    arXiv:2602.05371v3 Announce Type: replace Abstract: Oblique decision trees combine the transparency of trees with the power of multivariate decision boundaries, but learning high-quality oblique splits is NP-hard, and practical methods still rely on slow search or theory-free heu…