Metadata-Version: 2.1
Name: cfl
Version: 1.3.2
Summary: Causal Feature Learning (CFL) is an unsupervised algorithm designed to construct macro-variables from low-level data, while maintaining the causal relationships between these macro-variables. 
Home-page: https://github.com/eberharf/cfl
Author: Jenna Kahn and Iman Wahle
Author-email: imanwahle@gmail.com
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: Free for non-commercial use
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.7,<3.13
License-File: LICENSE.txt
Requires-Dist: tqdm
Requires-Dist: matplotlib>=3.3.4
Requires-Dist: tensorflow>=2.4.0
Requires-Dist: numpy>=1.19.5
Requires-Dist: scikit-learn>=1.0
Requires-Dist: jupyter
Requires-Dist: ipykernel
Requires-Dist: joblib>=0.16.0

See cfl.readthedocs.io for a full description
