DataOre
Lightweight data mining and machine-learning tools built on NumPy, pandas and SciPy.
0.11.1 correctness fixes
- ROC-AUC rejects non-finite prediction scores instead of stalling on NaN.
- AutoML fits scaling separately within each training fold and on the final training split; validation and holdout data no longer determine scaling.
- Failed or non-finite model evaluations cannot win model selection. Their errors remain available in the results and leaderboard.
- Regression leaderboards rank lower MSE first; prediction reuses the selected model's training statistics.
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Release files for dataore 0.11.1
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| dataore-0.11.1.tar.gz | 182.0 kB | Without provenance | Details for dataore-0.11.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| dataore-0.11.1-py3-none-any.whl | Python 3 | none | any | Details for dataore-0.11.1-py3-none-any.whl |
Total release size: 349.9 kB
Release files / dataore-0.11.1.tar.gz
| Download URL | dataore-0.11.1.tar.gz |
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| Size | 182.0 kB |
| Tags | Source |
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Release files / dataore-0.11.1-py3-none-any.whl
| Download URL | dataore-0.11.1-py3-none-any.whl |
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| Size | 167.9 kB |
| Tags | Python 3 |
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