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.
Metadata
Release files for dataore 0.11.1
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 |
|---|---|---|---|---|
| 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 |
|---|---|
| Size | 182.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
9bc284b602afda298df1af7b6ae9c0f8a824ef43a0ca440708dbe413f518e030
|
|
BLAKE2b-256 checksum How to use checksums |
b4da86746a1e95d84db89e277717f9de6600e2184688a158ecfe80231dfe3066
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.9
|
Release files / dataore-0.11.1-py3-none-any.whl
| Download URL | dataore-0.11.1-py3-none-any.whl |
|---|---|
| Size | 167.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
2bfa1e4d7ed54a63b0c56adce31eb8f1eddffb686f547bfd6404001130b190f3
|
|
BLAKE2b-256 checksum How to use checksums |
9dc9232b8d8043472c02a629128808d9ebf86c9ef27aa7acaf7032f43b44ae11
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.9
|
Security for dataore 0.11.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.