# Balanced Batch Sampling

> Source: https://sukruyusufkaya.com/en/glossary/balanced-batch-sampling
> Updated: 2026-05-13T19:59:31.781Z
> Type: glossary
> Category: veri-bilimi-ve-veri-yonetimi
**TLDR:** A sampling strategy that balances learning by maintaining a more controlled class distribution within each training batch.

<p>Balanced batch sampling is especially useful in deep learning to prevent the minority class from disappearing completely at the mini-batch level. Even if the full dataset is imbalanced, each mini-batch can be sampled in a more balanced way. This allows the model to see the minority class more consistently and makes the gradient signal more stable. However, the difference between training distribution and real distribution must be managed carefully. Balanced batch sampling is an effective bridge between data-level and optimization-level imbalance handling.</p>