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Genetic hyper-parameter selection for machine learning algorithms

Project description


mloptimizer is a Python module for hyper-parameters optimization in machine learning using genetic algorithms.


pip install mloptimizer


A simple example of use optimizing hyper-parameters in a decision tree classifier using the iris dataset:

from mloptimizer.genoptimizer import TreeOptimizer
from sklearn.datasets import load_iris

X, y = load_iris(return_X_y=True)
opt = TreeOptimizer(X, y, "output_log_file.log")
clf = opt.optimize_clf(10, 10)

Modules used

  • Deap - Genetic Algorithms
  • XGBoost - Gradient boosting classifier
  • sklearn - Usado para generar RSS





This project is under the LICENSE for more details.

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