# Mean Squared Error (MSE)

> Source: https://sukruyusufkaya.com/en/glossary/ortalama-kare-hata
> Updated: 2026-05-13T21:12:30.067Z
> Type: glossary
> Category: matematik-istatistik-optimizasyon
**TLDR:** A common regression loss function that averages the squared differences between predictions and true values.

<p>Mean Squared Error is one of the most commonly used loss functions in regression problems. Because it squares the difference between prediction and true value, it penalizes large errors more strongly. This can be useful because it encourages the model to reduce major deviations. However, it also makes the loss more sensitive to outliers. MSE is widely preferred because it combines statistical interpretability with a smooth differentiable structure that is convenient for optimization.</p>