DoubleML -- An Object-Oriented Implementation of Double Machine Learning in Python

• URL: http://arxiv.org/abs/2104.03220v1
• Date: Wed, 7 Apr 2021 16:16:39 GMT
• Title: DoubleML -- An Object-Oriented Implementation of Double Machine Learning in Python
• Authors: Philipp Bach, Victor Chernozhukov, Malte S. Kurz, Martin Spindler
• Abstract summary: DoubleML is an open-source Python library implementing the double machine learning framework of Chernozhukov et al. It contains functionalities for valid statistical inference on causal parameters when the estimation of parameters is based on machine learning methods. The package is distributed under the MIT license and relies on core libraries from the scientific Python ecosystem.
• Score: 1.4911092205861822
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: DoubleML is an open-source Python library implementing the double machine learning framework of Chernozhukov et al. (2018) for a variety of causal models. It contains functionalities for valid statistical inference on causal parameters when the estimation of nuisance parameters is based on machine learning methods. The object-oriented implementation of DoubleML provides a high flexibility in terms of model specifications and makes it easily extendable. The package is distributed under the MIT license and relies on core libraries from the scientific Python ecosystem: scikit-learn, numpy, pandas, scipy, statsmodels and joblib. Source code, documentation and an extensive user guide can be found at https://github.com/DoubleML/doubleml-for-py and https://docs.doubleml.org.

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