# Calibrated Classification

> Source: https://sukruyusufkaya.com/en/glossary/calibrated-classification
> Updated: 2026-05-13T20:02:16.963Z
> Type: glossary
> Category: makine-ogrenmesi
**TLDR:** An approach that aims to make a classifier’s probability outputs more consistent with true observed frequencies.

<p>Calibrated classification aims not only for correct class prediction, but also for trustworthy probability estimates. Probability calibration is especially important in domains such as credit scoring, medical decision support, and risk analysis. A model may achieve high accuracy while still producing probabilities that are overly confident or overly conservative. For that reason, calibration is a critical step in turning classification performance into operational decision quality.</p>