Metadata-Version: 2.1
Name: Interpretability
Version: 0.0.2
Summary: A selection of interpretable methods with logging and printouts
Home-page: https://github.com/egivental/resetInterpretability
Author: Emile Givental
Author-email: emilegivental@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Operating System :: OS Independent
Requires-Dist: cplex (>=12.9.0.0)
Requires-Dist: Prettytable (>=0.7.2)
Requires-Dist: pandas (>=0.24.2)
Requires-Dist: numpy (>=1.16.4)
Requires-Dist: sklearn (>=0.0)

This is a library with 3 interepretable machine learning methods, wrapped with logging and side by side comparison. They can be used as normal scikit learn models, with fit, predict, and find_accuracy methods. Or, a script can be run on a data set, which will run all three and return logs and accuracies.