python3-sklearn-genetic-opt Subpackage of python-sklearn-genetic-opt

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 hyperparameters tuning, and from RFE (Recursive Feature Elimination), Select From Model for feature selection. Sklearn-genetic-opt uses evolutionary algorithms from the DEAP (Distributed Evolutionary Algorithms in Python) 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. Documentation: https://sklearn-genetic-opt.readthedocs.io/

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