# Huber Regression

> Source: https://sukruyusufkaya.com/en/glossary/huber-regression
> Updated: 2026-05-13T21:01:00.439Z
> Type: glossary
> Category: makine-ogrenmesi
**TLDR:** A robust regression method that is more resistant to outliers than ordinary least squares.

<p>Huber regression is a robust regression approach that limits the influence of outliers by using squared loss for small errors and linear loss for large ones. This structure produces more stable estimates than ordinary linear regression without switching to an overly aggressive outlier-focused strategy. It is especially useful in settings that contain measurement noise, data-entry issues, or unusual observations in the tail of the distribution. It provides a practical bridge between robust statistics and applied machine learning.</p>