Beyond Accuracy: Quantifying the Production Fragility Caused by Excessive, Redundant, and Low-Signal Features in Regression (www.marktechpost.com)

<p>At first glance, adding more features to a model seems like an obvious way to improve performance. If a model can learn from more information, it should be able to make better predictions. In practice, however, this instinct often introduces hidden structural risks. Every additional feature creates another dependency on upstream data pipelines, external systems, [&#8230;]</p>
<p>The post <a href="https://www.marktechpost.com/2026/03/08/beyond-accuracy-quantifying-the-production-fragility-caused-by-excessive-redundant-and-low-signal-features-in-regression/">Beyond Accuracy: Quantifying the Production Fragility Caused by Excessive, Redundant, and Low-Signal Features in Regression</a> appeared first on <a href="https://www.marktechpost.com">MarkTechPost</a>.</p>