Hyperparameters tuning and feature selection
scikit-learn models hyperparameters tuning and feature selection, using evolutionary algorithms. This is meant to be an alternative to popular methods inside scikit-learn such as Grid Search and Randomized Grid Search for hyperparameteres tuning, and from RFE, Select From Model for feature selection. Sklearn-genetic-opt uses evolutionary algorithms from the DEAP package to choose the set of hyperparameters that optimizes (max or min) the cross-validation scores, it can be used for both regression and classification problems.
Release | Stable | Testing |
---|---|---|
Fedora Rawhide | 0.10.1-7.fc40 | - |
Fedora 40 | 0.10.1-7.fc40 | - |
Fedora 39 | 0.10.1-5.fc39 | - |
Fedora 38 | 0.9.0-4.fc38 | - |
You can contact the maintainers of this package via email at
python-sklearn-genetic-opt dash maintainers at fedoraproject dot org
.