forecastEval
forecastEval is an open-source Python library that provides a lightweight and unified framework for rigorous evaluation of time-series forecasts.
The library is designed to address common shortcomings in forecasting practice, including insufficient baseline comparison, over-reliance on aggregated error metrics, and lack of statistical validation of performance differences.
Key Features
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Baseline-aware evaluation
- Automatic comparison against persistence (naïve) and seasonal naïve baselines
- Mean Absolute Scaled Error (MASE) and skill scores for interpretable performance assessment
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Horizon-stratified analysis
- User-defined forecast horizon windows
- Detection of horizon-dependent performance degradation
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Statistical validation
- Diebold–Mariano test for forecast comparison
- Autocorrelation-adjusted variance estimation
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Interpretative reporting
- Clear PASS / FAIL recommendations for model deployment
- Human-readable console summaries
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Interactive HTML reports
- Collapsible sections, visual summaries, and horizon-wise breakdowns
Installation
pip install forecastEval
1 maintainer
Metadata
1 maintainer
Release files for forecastEval 0.2.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| forecasteval-0.2.4.tar.gz | 27.2 kB | Without provenance | Details for forecasteval-0.2.4.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| forecasteval-0.2.4-py3-none-any.whl | Python 3 | none | any | Details for forecasteval-0.2.4-py3-none-any.whl |
Total release size: 55.3 kB
Release files / forecasteval-0.2.4.tar.gz
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Release files / forecasteval-0.2.4-py3-none-any.whl
| Download URL | forecasteval-0.2.4-py3-none-any.whl |
|---|---|
| Size | 28.1 kB |
| Tags | Python 3 |
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No |
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twine/6.2.0 CPython/3.9.6
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Security for forecastEval 0.2.4
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