Metadata-Version: 2.1
Name: SimpleGP
Version: 0.9.5
Summary: UNKNOWN
Home-page: https://github.com/marcovirgolin/SimpleGP
Author: Marco Virgolin
Author-email: marco.virgolin@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: numpy (>=1.16.1)
Requires-Dist: sklearn

# Simple Genetic Programming 
### For Symbolic Regression
This Python 3 code is a simple implementation of genetic programming for symbolic regression, and has been developed for educational purposes.

## Dependencies
`numpy` & `sklearn`. The file `test.py` shows an example of usage.

## Installation
You can install it with pip using `python3 -m pip install --user simplegp`, or locally by downloading the code and running `python3 setup.py install --user`.

## Reference
If you use this code, please support our research by citing the [paper](https://arxiv.org/abs/2004.11170) that used it as a base to develop a [multi-objective version](https://github.com/marcovirgolin/pyNSGP):

> M. Virgolin, A. De Lorenzo, E. Medvet, F. Randone. "Learning a Formula of Interpretability to Learn Interpretable Formulas". arXiv preprint arXiv:2004.11170 (2020)


