# SMOTE

> Source: https://sukruyusufkaya.com/en/glossary/smote
> Updated: 2026-05-13T20:58:39.734Z
> Type: glossary
> Category: veri-bilimi-ve-veri-yonetimi
**TLDR:** A widely used balancing technique that generates new synthetic examples for the minority class from existing ones.

<p>SMOTE is one of the best-known synthetic resampling techniques for imbalanced data problems. It generates new synthetic minority-class samples by interpolating between existing minority examples. This can provide more varied learning signals than simple duplication. However, in complex class boundaries or noisy data, it may generate misleading samples and harm model behavior. For that reason, while SMOTE is a strong starting technique, it should be applied with careful attention to the structure of the data.</p>