uq-metrics
Uncertainty quantification metrics for model evaluation. Pure NumPy implementation.
Installation
pip install uq-metrics
For plotting support:
pip install uq-metrics[plot]
Usage
from uq_metrics import auroc, ece, brier_score, aurc
import numpy as np
y_true = np.array([0, 0, 1, 1, 1])
y_scores = np.array([0.2, 0.3, 0.6, 0.8, 0.9])
auroc(y_true, y_scores) # Area Under ROC Curve
ece(y_true, y_scores) # Expected Calibration Error
brier_score(y_true, y_scores) # Brier Score
# With plotting
score, ax = auroc(y_true, y_scores, plot=True)
Available Metrics
auroc- Area Under ROC Curveece- Expected Calibration Errorbrier_score- Brier Scoreaurc- Area Under Risk-Coverage Curveerror_vs_abstention- Error rates at abstention levelsoptimal_abstention- Find optimal abstention threshold
1 maintainer
Metadata
1 maintainer
Release files for uq-metrics 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| uq_metrics-0.1.0.tar.gz | 8.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| uq_metrics-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 17.6 kB
Release files / uq_metrics-0.1.0.tar.gz
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Release files / uq_metrics-0.1.0-py3-none-any.whl
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| Size | 9.6 kB |
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