The Equation Tree package is an equation toolbox with symbolic regression in mind. It represents expressions as incomplete binary trees and has various features tailored towards testing symbolic regression algorithms or training models. The main features are:
- Equation sampling (including priors)
- Feature Extraction from equation distributions
- Distance metrics between equations
Check out the documentation at https://autoresearch.github.io/equation-tree.
This project is in active development by the Autonomous Empirical Research Group (package developers: Ioana Marinescu and Younes Strittmatter, PI: Sebastian Musslick. This research program is supported by Schmidt Science Fellows, in partnership with the Rhodes Trust, as well as the Carney BRAINSTORM program at Brown University.