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)
