mloptimizer 0.5.1

Genetic hyper-parameter selection for machine learning algorithms

mloptimizer

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

Installation

pip install mloptimizer

Quickstart

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

Wiki

TODO [Wiki](DOCUMENTATION TODO)

Authors

• Antonio Caparrini - Owner - caparrini

License

This project is under the LICENSE for more details.