Factual package intelligence from PyPI

skheros 0.4.2 package intelligence

The Heuristic Evolutionary Rule Optimization System (HEROS) is a supervised rule-based machine learning algorithm designed to agnostically model diverse 'structured' data problems and yield compact human interpretable solutions. This implementation is scikit-learn compatible.

pip install skheros

Current version
0.4.2
Python requirement
>=3.9
License
Other/Proprietary License
Distribution type
Pure Python wheel
Release files
2 (1 wheels, 1 source)
Download size
184.5 KiB
Release history
5 releases with files
Median release cadence
47 days

skheros dependencies

PyPI declares 13 unique dependency rules for this release. Environment markers are shown when supplied by the project.

  1. numpy
  2. pandas
  3. scikit-learn
  4. matplotlib
  5. seaborn
  6. scipy
  7. skrebate
  8. networkx

Compatibility and release files

skheros publishes 1 wheel and 1 source archive for version 0.4.2. Wheel platform tags: any.

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

Security snapshot for skheros 0.4.2

An OSV query completed on and found 0 known vulnerabilities affecting this version. 0 advisories are classified as critical. 0 advisories appear in the CISA Known Exploited Vulnerabilities catalog.

Release activity and sources

PyPI lists 5 releases with files. The first dated release is ; 3 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .