Name | itea JSON |
Version |
1.1.2
JSON |
| download |
home_page | |
Summary | Interaction-Transformation Evolutionary Algorithm for Symbolic Regression. |
upload_time | 2023-07-05 13:53:01 |
maintainer | |
docs_url | None |
author | Guilherme Aldeia |
requires_python | >=3.7 |
license | BSD-3-Clause |
keywords |
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VCS |
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bugtrack_url |
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requirements |
No requirements were recorded.
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Travis-CI |
No Travis.
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coveralls test coverage |
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# 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).
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"description": "# itea-python\n\n<img src=\"https://galdeia.github.io/itea-python/_static/itea-logo.png\" alt=\"drawing\" width=\"300\"/><br>\n\n![code coverage](https://galdeia.github.io/itea-python/_images/coverage.svg)\n![python version](https://galdeia.github.io/itea-python/_images/pythonversion.svg)\n\n[![PyPI version](https://badge.fury.io/py/itea.svg)](https://badge.fury.io/py/itea)\n[![Documentation Status](https://readthedocs.org/projects/itea-python/badge/?version=latest)](https://itea-python.readthedocs.io/en/latest/?badge=latest)\n\nitea is a python implementation of the Interaction-Transformation Evolutionary\nAlgorithm described in the paper \"Franca, F., & Aldeia, G. (2020).\nInteraction-Transformation Evolutionary Algorithm for Symbolic Regression.\nEvolutionary Computation, 1-25.\"\n\nThe Interaction-Transformation (IT) representation is a step towards obtaining\nsimpler and more interpretable results, searching in the mathematical\nequations space by means of an evolutionary strategy.\n\nTogether with ITEA for Classification and Regression, we provide a\nmodel-specific explainer based on the Partial Effects to help users get a\nbetter understanding of the resulting expressions.\n\nThis implementation is based on the scikit-learn package and the implementations\nof the estimators follow their guidelines.\n\n\n> **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).\n\n## Documentation\n\nDocumentation is available at [readthedocs](https://itea-python.readthedocs.io/en/latest).\n\n",
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