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新的TrIM算法增强了降维和回归

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种名为TrIM（Transformed Iterative Mondrian Forests）的新算法，用于高效的基于梯度的线性降维和高维回归。该方法利用Mondrian森林通过估计期望梯度外积（EGOP）来识别相关的特征子空间。TrIM算法通过基于EGOP估计更新特征和权重来迭代地优化Mondrian森林，并提供了理论上的收敛性和一致性保证。 AI

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新的TrIM算法增强了降维和回归

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报道来源 [1]

  1. arXiv stat.ML TIER_1 English(EN) · Ricardo Baptista, Eliza O'Reilly, Yangxinyu Xie ·

    TrIM：用于基于梯度的降维和高维回归的变换迭代蒙德里安森林

    arXiv:2407.09964v2 Announce Type: replace-cross Abstract: We propose a computationally efficient algorithm for gradient-based linear dimension reduction and high-dimensional regression. The algorithm initially computes a Mondrian forest and uses this estimator to identify a relev…

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