doa is a tool to find domains of applicability of machine learning models. These domains are expressed using the features that the model uses to represent the input data.
The details of the method can be found in our manuscript titled Outlier-Based Domain of Applicability Identification for Materials Property Prediction Models at https://doi.org/10.26434/chemrxiv-2023-pmrfw-v2.
How the test predictions improve as we remove data corresponding to 'difficult' domains identified by our method. |
Cretae a conda environment,
conda env create -f environment.yml
Go to the doa directory where setup.py is located and type,
pip install .
A complete example is given in the tutorials/1.getting_started.ipynb
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