English(EN) The limits of interpretability in multiple linear regression

论文揭示线性回归模型的可解释性限制

作者 PulseAugur 编辑部 · [2 个来源] · 2026-06-14 20:50

一篇新发表在arXiv上的论文探讨了多重线性回归模型在可解释性方面的局限性，特别是在处理多重共线性时。该研究从理论上分析了相关的输入特征如何导致权重不稳定和振荡，从而阻碍物理解释。虽然Ridge正则化可以抑制这些不稳定的模式，但论文强调，即使在这些比深度神经网络更简单的模型中，解释所得权重时仍需谨慎。 AI

影响强调了即使是简单的线性模型在解释方面也存在挑战，提示在从AI输出中得出结论时需要谨慎。

排序理由该集群包含一篇预印本学术论文，讨论了机器学习模型的理论和数值分析。

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报道来源 [2]

arXiv cs.LG TIER_1 English(EN) · Anand Sharma, Chen Liu, Daniele Coslovich, Misaki Ozawa · 2026-06-16 04:00

The limits of interpretability in multiple linear regression

arXiv:2606.16013v1 Announce Type: cross Abstract: Interpreting machine-learning models has attracted increasing attention, particularly in the physical sciences, where one often seeks to understand the underlying mechanisms rather than merely make predictions. Multiple linear reg…
arXiv stat.ML TIER_1 English(EN) · Misaki Ozawa · 2026-06-14 20:50

The limits of interpretability in multiple linear regression

Interpreting machine-learning models has attracted increasing attention, particularly in the physical sciences, where one often seeks to understand the underlying mechanisms rather than merely make predictions. Multiple linear regression is often regarded as an interpretable alte…

报道来源 [2]

The limits of interpretability in multiple linear regression

The limits of interpretability in multiple linear regression

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