Metadata-Version: 2.1
Name: sage-importance
Version: 0.0.5
Summary: For calculating global feature importance using Shapley values.
Home-page: https://github.com/iancovert/sage/
Author: Ian Covert
Author-email: icovert@cs.washington.edu
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: tqdm
Requires-Dist: joblib


        SAGE (Shapley Additive Global importancE) is a game theoretic approach 
        for understanding black-box machine learning models. It quantifies each 
        feature's importance based on the predictive power it contributes, and 
        it accounts for complex interactions using the Shapley value from 
        cooperative game theory. See the 
        [GitHub page](https://github.com/iancovert/sage/) for examples, and see 
        the [paper](https://arxiv.org/abs/2004.00668) for more details.
    
