Definition: Scoring rule
Index: The Book of Statistical Proofs ▷ General Theorems ▷ Machine learning ▷ Scoring rules ▷ Scoring rule
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Metadata: ID: D192 | shortcut: sr | author: KarahanS | date: 2024-02-28, 20:50.
Definition: A scoring rule is any extended real-valued function $\mathbf{S}: \mathcal{Q} \times \Omega \rightarrow \mathbb {R}$ where $\mathcal{Q}$ is a family of probability distributions over the space $\Omega$, such that $\mathbf{S}(Q, \cdot) $ is $\mathcal{Q}$-quasi-integrable for all $Q \in \mathcal{Q}$. Output of the function $\mathbf{S}(Q, y)$ represents the loss or penalty when the forecast $Q \in \mathcal{Q}$ is issued and the observation $y \in \Omega$ is realized.
- Bálint Mucsányi, Michael Kirchhof, Elisa Nguyen, Alexander Rubinstein, Seong Joon Oh (2023): "Proper/Strictly Proper Scoring Rule"; in: Trustworthy Machine Learning; URL: https://trustworthyml.io/; DOI: 10.48550/arXiv.2310.08215.
- Wikipedia (2024): "Scoring rule"; in: Wikipedia, the free encyclopedia, retrieved on 2024-02-28; URL: https://en.wikipedia.org/wiki/Scoring_rule.
Metadata: ID: D192 | shortcut: sr | author: KarahanS | date: 2024-02-28, 20:50.