CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox

Artelt A (2019)
Bielefeld University.

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**CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox**
ceml is a Python toolbox for computing counterfactuals. Counterfactuals can be used to explain the predictions of machine learning models. It supports many common machine learning frameworks: - scikit-learn - PyTorch - Keras - Tensorflow Furthermore, ceml is easy to use and can be extended very easily. See the documentation and user guide for more information on how to use and extend ceml.
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Artelt A. CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox . Bielefeld University; 2019.
Artelt, A. (2019). CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox . Bielefeld University. doi:10.4119/unibi/2936468
Artelt, A. (2019). CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox . Bielefeld University.
Artelt, A., 2019. CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox , Bielefeld University.
A. Artelt, CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox , Bielefeld University, 2019.
Artelt, A.: CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox . Bielefeld University (2019).
Artelt, André. CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox . Bielefeld University, 2019.
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2019-07-16T09:40:16Z

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