---
title: Multicalibration
type: concept
frequency: 2
papers_count: 2
related_concepts:
  - Intersectional Fairness
  - Subgroup Fairness
  - Algorithmic Fairness
  - Fairness Gerrymandering
tags:
  - concept
---
# Multicalibration

## Definition

Eine spezialisierte Fairness-Mitigationstechnik, die gewährleistet, dass Modellvorhersagen für verschiedene intersektionale Subgruppen kalibriert sind, unabhängig davon, ob diese Gruppen explizit in den Trainingsdaten vertreten sind.

## Co-occurrence

| Konzept | Gemeinsame Papers |
|---------|------------------|
| [[Intersectional Fairness]] | 2 |
| [[Subgroup Fairness]] | 2 |
| [[Algorithmic Fairness]] | 1 |
| [[Fairness Gerrymandering]] | 1 |

## Papers

- [[A Survey on Intersectional Fairness in Machine Learning- Notions, Mitigation, and Challenges]]
- [[A Survey on Intersectional Fairness in Machine Learning- Notions, Mitigation, and Challenges (Gohar_2023_Survey)]]

