Metadata-Version: 2.1
Name: PySR3
Version: 0.3.3
Summary: Python Library for Sparse Relaxed Regularized Regression.
Home-page: https://github.com/aksholokhov/pysr3
Author: Aleksei Sholokhov
Author-email: aksh@uw.edu
License: GNU GPLv3
Platform: UNKNOWN
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy (>=1.21.1)
Requires-Dist: pandas (>=1.3.1)
Requires-Dist: scipy (>=1.7.1)
Requires-Dist: PyYAML (>=5.4.1)
Requires-Dist: scikit-learn (>=0.24.2)
Requires-Dist: ipython
Provides-Extra: dev
Requires-Dist: sphinx ; extra == 'dev'
Requires-Dist: sphinx-rtd-themenbconvert ; extra == 'dev'
Requires-Dist: nbformat ; extra == 'dev'
Requires-Dist: pytest ; extra == 'dev'
Provides-Extra: docs
Requires-Dist: sphinx ; extra == 'docs'
Requires-Dist: sphinx-rtd-themenbconvert ; extra == 'docs'
Requires-Dist: nbformat ; extra == 'docs'
Provides-Extra: test
Requires-Dist: pytest ; extra == 'test'

This package implements classic and novel feature selection algorithms  for linear and mixed-effect models. It supports many widely used regularization techniques, like LASSO, A-LASSO, CAD and SCAD. See README.md for details and examples.