ECNet: machine learning models for fuel property prediction
ECNet is an open source Python package for creating machine learning models to predict fuel properties. ECNet comes bundled with a variety of fuel property datasets, including cetane number, yield sooting index, and research/motor octane number. ECNet was built using the PyTorch library, allowing easy implementation of our models in your existing ML pipelines.
Future plans for ECNet include:
- Implementating RDKit to train using molecular fingerprints
- Leveraging additional QSPR-generation software packages (e.g. Mordred)
- A graphical user interface
Installation and Usage
Contributing, Reporting Issues, and Other Support:
To contribute to ECNet, make a pull request. Contributions should include tests for new features added, as well as extensive documentation.
To report problems with the software or feature requests, file an issue. When reporting problems, include information such as error messages, your OS/environment and Python version.