ML hyperparameters tuning and features selection, using evolutionary algorithms.
sklearn_genetic.callbacks.ThresholdStopping
, sklearn_genetic.callbacks.ConsecutiveStopping
and sklearn_genetic.callbacks.DeltaThreshold
.sklearn_genetic.algorithms
for more control over their options, rather that taking the deap.algorithms module
.sklearn_genetic.plots
module and added the function sklearn_genetic.plots.plot_search_space
,
this function plots a mixed counter, scatter and histogram plots over all the fitted hyperparameters and their cross-validation score.best_params_
and best_estimator_
properties after fitting GASearchCV.refit
, pre_dispatch
and error_score
.continuous_parameters
, categorical_parameters
and integer_parameters
in GASearchCV, replacing them with param_grid
.