SR-electrolytes
Symbolic Regression on High-throughput electrolyte data.
This repositrory contains modules and an example to train symbolic regression models, following the methodology in the article:
Flores, Eibar, et al. "Learning the laws of lithium-ion transport in electrolytes using symbolic regression." Digital Discovery 1.4 (2022): 440-447. DOI:10.1039/D2DD00027J
Interactive plot of model predictions
We have set-up a small site with an interactive plot illustrating the predictions of the model foun in the article. To visit follow this link: EFlores2022_SR2022
How to use
We have drafted a Jupyter Notebook explaining how to use the modules. You can find it here. The modules use the following dependencies:
- numpy
- sympy
- pandas
- scikit-learn
- autofeat
Aknowledgements
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 957189.