A package for Causal Data Science.
Causal inference is the process of identifying and estimating the causal effect of a given treatment for a chosen outcome. To formally describe the relationship between a cause and its effect, a causal model must be constructed from the available data and the experts' prior knowledge in a process called causal discovery. This library is intended to collect, organize and exploit state of the art methodology to enable causal data science.
To use this software, run the following cargo command in your project directory:
cargo add causal-hub
Or add the following lines to your Cargo.toml:
[dependencies]
causal-hub = "^0.1"The official documentation is available here.
All notable changes to this project will be documented in the CHANGELOG.
To contribute to this software refer to CONTRIBUTING.
To cite this software refer to CITATION or click on Cite this repository in the GitHub repository. Read more.
This software is distributed under the terms of both the Apache License (Version 2.0) and the MIT license.
See LICENSE-APACHE and LICENSE-MIT for details.
This software follows the SemVer specification.