Factual package intelligence from PyPI

mloptimizer 0.9.4 package intelligence

mloptimizer is a Python library for optimizing hyperparameters of machine learning algorithms using genetic algorithms.

pip install mloptimizer

Current version
0.9.4
Python requirement
<3.14,>=3.9
License
MIT License
Distribution type
Pure Python wheel
Release files
2 (1 wheels, 1 source)
Download size
190.1 KiB
Release history
39 releases with files
Median release cadence
4 days

mloptimizer dependencies

PyPI declares 80 unique dependency rules for this release. Environment markers are shown when supplied by the project.

  1. catboost >=1.1.1
  2. deap >=1.3.3
  3. joblib >=1.2.0
  4. kaleido ==0.2.1
  5. numpy
  6. pandas >=1.5.3
  7. plotly >=5.15.0
  8. matplotlib <3.10.0
  9. python-dateutil >=2.8.1
  10. pytz >=2022.7.1
  11. scikit-learn <=1.5.2,>=1.2.1
  12. scipy >=1.10.0
  13. seaborn ==0.12.2
  14. six >=1.15.0
  15. tqdm
  16. xgboost >=1.7.3

The compact report shows 25 of 80 declarations. The interactive dependency graph loads the complete metadata.

Compatibility and release files

mloptimizer publishes 1 wheel and 1 source archive for version 0.9.4. Wheel platform tags: any.

Declared Python classifiers: 3.10, 3.11, 3.12, 3.13, 3.9.

Release activity and sources

PyPI lists 39 releases with files. The first dated release is ; 7 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .

2 historical releases are fully yanked in PyPI metadata.