Neural Networks Optimized by Genetic Algorithms for Data Analysis (NNOGADA)
nnogada is a Python package that performs hyperparemeter tuning for artificial neural networks, particularly for Multi Layer Perceptrons, using simple genetic algorithms. Useful for generate better neural network models for data analysis. Currently, only works with feedforward neural networks in tensorflow.keras (classification and regression) and torch (regression at this moment).
You can try to install nnogada in your computer:
$ git clone https://github.com/igomezv/nnogada
$ cd nnogada
$ pip3 install -e .
then you can delete the cloned repo because you must have nnogada installed locally.
Other way to install nnogada (without clonning) is:
$ pip3 install -e git+https://github.com/igomezv/nnogada#egg=nnogada
If you use the code, please cite the paper Gómez-Vargas, I., Andrade, J. B., & Vázquez, J. A. (2023). Neural networks optimized by genetic algorithms in cosmology. Physical Review D, 107(4), 043509.
Contributions are welcome!
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Release files for nnogada 0.9.1.3
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Release files / nnogada-0.9.1.3.tar.gz
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