causalml 0.15.1

Python Package for Uplift Modeling and Causal Inference with Machine Learning Algorithms

08-09-2021 187 words One minute 0 views

Contents

Python Package for Uplift Modeling and Causal Inference with Machine Learning Algorithms

Stars: 4791, Watchers: 4791, Forks: 753, Open Issues: 55

The uber/causalml repo was created 4 years ago and the last code push was 6 days ago.
The project is very popular with an impressive 4791 github stars!

How to Install causalml

You can install causalml using pip

pip install causalml

or add it to a project with poetry

poetry add causalml

Package Details

Author: Huigang Chen, Totte Harinen, Jeong-Yoon Lee, Jing Pan, Mike Yung, Zhenyu Zhao
License: None
Homepage: None
PyPi:: https://pypi.org/project/causalml/
GitHub Repo:: https://github.com/uber/causalml

Classifiers

No causalml pypi packages just yet.

Errors

A list of common causalml errors.

Code Examples

Here are some causalml code examples and snippets.

GitHub Issues

The causalml package has 55 open issues on GitHub

How can we get the probability for each class with basexclassifier?
AttributeError: module 'causalml.inference.tree.uplift' has no attribute 'bootstrap'
Add Python 3.10 to the testing
Add structural and covariate information to counterfactual unit selection
UpliftRandomForestClassifier with n_jobs=-1 creates copies of data
Package requires old scipy version

See more issues on GitHub