semvec/pypi-packages huggingface dataset:
itea 1.1.2
Interaction-Transformation Evolutionary Algorithm for Symbolic Regression.
License: BSD-3-Clause
Requires Python: >=3.7

# itea-python

<img src="https://galdeia.github.io/itea-python/_static/itea-logo.png" alt="drawing" width="300"/><br>

![code coverage](https://galdeia.github.io/itea-python/_images/coverage.svg)
![python version](https://galdeia.github.io/itea-python/_images/pythonversion.svg)

[![PyPI version](https://badge.fury.io/py/itea.svg)](https://badge.fury.io/py/itea)
[![Documentation Status](https://readthedocs.org/projects/itea-python/badge/?version=latest)](https://itea-python.readthedocs.io/en/latest/?badge=latest)

itea is a python implementation of the Interaction-Transformation Evolutionary
Algorithm described in the paper "Franca, F., & Aldeia, G. (2020).
Interaction-Transformation Evolutionary Algorithm for Symbolic Regression.
Evolutionary Computation, 1-25."

The Interaction-Transformation (IT) representation is a step towards obtaining
simpler and more interpretable results, searching in the mathematical
equations space by means of an evolutionary strategy.

Together with ITEA for Classification and Regression, we provide a
model-specific explainer based on the Partial Effects to help users get a
better understanding of the resulting expressions.

This implementation is based on the scikit-learn package and the implementations
of the estimators follow their guidelines.


> **OBS:** There also exists a [high-performing Haskell implementation (that comes with a python wrapper)](https://github.com/folivetti/ITEA) by [@folivetti](https://github.com/folivetti/ITEA).

## Documentation

Documentation is available at [readthedocs](https://itea-python.readthedocs.io/en/latest).