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Uplift modeling implementation

Project description

Documentation Status Build Status PyPI - Python Version GitHub

DocumentationLicenseHow to contributeUplift datasetsInspiration

Installation

Install from PyPI

pip install pyuplift

Install from source code

git clone https://github.com/duketemon/pyuplift.git
cd pyuplift
python setup.py install

How to contribute

Any contributions are always welcomed. There is a lot of ways how you can help to the project.

Uplift datasets

Compatible with

Inspiration

References

  • Devriendt F, Moldovan D, Verbeke W. A literature survey and experimental evaluation of the state-of-the-art in uplift modeling: A stepping stone toward the development of prescriptive analytics. Big data. 2018 Mar 1;6(1):13-41.
  • Weisberg HI, Pontes VP. Post hoc subgroups in clinical trials: Anathema or analytics?. Clinical trials. 2015 Aug;12(4):357-64.
  • Lo VS. The true lift model: a novel data mining approach to response modeling in database marketing. ACM SIGKDD Explorations Newsletter. 2002 Dec 1;4(2):78-86.
  • Guelman L, Guillén M, Pérez-Marín AM. A decision support framework to implement optimal personalized marketing interventions. Decision Support Systems. 2015 Apr 1;72:24-32.
  • Tian L, Alizadeh AA, Gentles AJ, Tibshirani R. A simple method for estimating interactions between a treatment and a large number of covariates. Journal of the American Statistical Association. 2014 Oct 2;109(508):1517-32.

Project details


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