agreement_statistics
Compute ID accuracy, pairwise ID/OOD agreement, and clipped probit statistics for agreement-on-the-line experiments.
- License 许可
- Apache-2.0
- 最近更新
- 2026-09-03
- Stars
- ★ 351
- Forks
- 27
01 前言 Front Matter
- name
- agreement_statistics
- description
- Compute ID accuracy, pairwise ID/OOD agreement, and clipped probit statistics for agreement-on-the-line experiments.
02 资源文件 2
03 SKILL.md 正文
Agreement Statistics
Use this skill after a prediction table has been validated. It preserves the paper's estimator boundary by computing OOD agreement from predictions only and never using OOD labels.
Inputs
- Normalized prediction table from
prediction_table_contracts. - Optional clipping epsilon for probit transforms.
Outputs
- Per-model ID accuracies.
- Pairwise ID and OOD agreement fractions.
- Probit-transformed accuracies and agreements.
Workflow
- Compute ID accuracy from ID labels and ID predictions.
- Compute unordered pairwise agreement on ID predictions.
- Compute unordered pairwise agreement on OOD predictions.
- Clip probabilities before inverse-normal transformation.
Validation
Run python tests/test_agreement_statistics.py from this skill directory.
Limitations
This skill does not fit the agreement line or solve ALine-D.
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