def make_mode_nested_cv(data, seed, configuration, num_run, inner_folds, outer_folds): global evaluator evaluator = NestedCVEvaluator(data, configuration, inner_cv_folds=inner_folds, outer_cv_folds=outer_folds, seed=seed, num_run=num_run, **_get_base_dict()) evaluator.fit() signal.signal(15, empty_signal_handler) evaluator.finish_up()
def make_mode_nested_cv(data, seed, configuration, num_run, inner_folds, outer_folds, output_dir): global evaluator evaluator = NestedCVEvaluator(data, output_dir, configuration, inner_cv_folds=inner_folds, outer_cv_folds=outer_folds, seed=seed, all_scoring_functions=False, num_run=num_run, **_get_base_dict()) loss, opt_pred, valid_pred, test_pred = evaluator.fit_predict_and_loss() evaluator.finish_up(loss, opt_pred, valid_pred, test_pred)
def make_mode_nested_cv(data, seed, configuration, num_run, inner_folds, outer_folds): global evaluator evaluator = NestedCVEvaluator(data, configuration, inner_cv_folds=inner_folds, outer_cv_folds=outer_folds, seed=seed, num_run=num_run, **_get_base_dict()) evaluator.fit() signal.signal(15, empty_signal_handler) evaluator.finish_up()
def make_mode_nested_cv(data, seed, configuration, num_run, inner_folds, outer_folds, output_dir): global evaluator evaluator = NestedCVEvaluator(data, output_dir, configuration, inner_cv_folds=inner_folds, outer_cv_folds=outer_folds, seed=seed, all_scoring_functions=False, num_run=num_run, **_get_base_dict()) loss, opt_pred, valid_pred, test_pred = evaluator.fit_predict_and_loss() evaluator.finish_up(loss, opt_pred, valid_pred, test_pred)