Metadata-Version: 2.1
Name: skga
Version: 0.0.3
Summary: The python package implementing the HyperBRKGA algorithm optimizes hyperparameters of machine learning algorithms through a hybrid approach based on genetic algorithms.
Home-page: https://github.com/MLRG-CEFET-RJ/skga
Author: Leonardo Sauberman, João Pedro Nogueira, Eduardo Bezerra
Author-email: leonardo.moraes@aluno.cefet-rj.br, joao.carneiro@aluno.cefet-rj.br, ebezerra@cefet-rj.br
License: BSD License
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE

# HyperBKRGA

## Setting up the Environment 

To run any code in this repository, it is necessary to follow these steps:

- Create and activate a virtual environment:

```bash
$ python -m venv venv
$ venv/Scripts/activate
```

- Install the dependencies contained in `requirements.txt`
```bash
pip install -r requirements.txt
```

## Basic Example
With the environment set up, it is possible to run the simplest example as follows:

```bash
$ py ./src/examples/basic-example.py
```

## Experiments
To reproduce the experiments carried out in this work, run the `src/main.py` file.
Note that it is a time-consuming program.


