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GeneticPy is an optimizer that uses a genetic algorithm to quickly search through custom parameter spaces for optimal solutions.

Project description

GeneticPy

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GeneticPy is an optimizer that uses a genetic algorithm to quickly search through custom parameter spaces for optimal solutions.

Installation

GeneticPy requires Python 3.4+

pip install geneticpy

Example Usage:

A brief example to get you started is included below:

def loss_function(params):
  if params['type'] == 'add':
    return params['x'] + params['y']
  elif params['type'] == 'multiply':
    return params['x'] * params['y']

param_space = {'type': geneticpy.ChoiceDistribution(choice_list=['add', 'multiply']),
               'x': geneticpy.UniformDistribution(low=5, high=10, q=1),
               'y': geneticpy.GaussianDistribution(mean=0, standard_deviation=1)}

results = geneticpy.optimize(loss_function, param_space, size=200, generation_count=500, verbose=True)
best_params = results['top_params']
loss = results['top_score']
total_time = results['total_time']

PyPi Project

https://pypi.org/project/geneticpy/

Contact

Please feel free to email me at brandonschabell@gmail.com with any questions or feedback.

Project details


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