Factual package intelligence from PyPI

Beat-ML1 0.13.1 package intelligence

This package contains several methods for calculating Conditional Average Treatment Effects

pip install beat-ml1

Current version
0.13.1
Python requirement
Not declared
License
MIT
Distribution type
Includes compiled wheel
Release files
2 (1 wheels, 1 source)
Download size
2.3 MiB
Release history
1 releases with files
Median release cadence
Not enough dated releases

Beat-ML1 dependencies

PyPI declares 22 unique dependency rules for this release. Environment markers are shown when supplied by the project.

  1. numpy
  2. scipy >1.4.0
  3. scikit-learn <1.2,>0.22.0
  4. sparse
  5. joblib >=0.13.0
  6. statsmodels >=0.10
  7. pandas
  8. shap <0.41.0,>=0.38.1
  9. lightgbm

Compatibility and release files

Beat-ML1 publishes 1 wheel and 1 source archive for version 0.13.1. Wheel platform tags: macosx_10_9_x86_64.

Declared Python classifiers: 3.6, 3.7, 3.8, 3.9.

Metadata completeness

PyPI does not currently declare: Python requirement. PyDeps marks these fields as unknown instead of guessing values.

Release activity and sources

PyPI lists 1 release with files. The first dated release is ; 1 release falls within the 365 days preceding the latest dated release. The current release files were uploaded on .