Python HoldoutEvaluatorの例

コード例 #1

ファイル: base_interface.py プロジェクト: Allen1203/auto-sklearn

def make_mode_holdout(data, seed, configuration, num_run, output_dir):
    global evaluator
    evaluator = HoldoutEvaluator(data, output_dir, configuration,
                                 seed=seed,
                                 num_run=num_run,
                                 all_scoring_functions=False,
                                 **_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)

コード例 #2

ファイル: base_interface.py プロジェクト: stokasto/auto-sklearn

def make_mode_holdout_iterative_fit(data, seed, configuration, num_run):
    global evaluator
    evaluator = HoldoutEvaluator(data, configuration, seed=seed, num_run=num_run, **_get_base_dict())
    evaluator.iterative_fit()
    signal.signal(15, empty_signal_handler)
    evaluator.finish_up()

    backend = Backend(None, os.getcwd())
    if os.path.exists(backend.get_model_dir()):
        backend.save_model(evaluator.model, num_run, seed)

コード例 #3

ファイル: base_interface.py プロジェクト: Allen1203/auto-sklearn

def make_mode_holdout_iterative_fit(data, seed, configuration, num_run,
                                    output_dir):
    global evaluator
    evaluator = HoldoutEvaluator(data, output_dir, configuration,
                                 seed=seed,
                                 num_run=num_run,
                                 all_scoring_functions=False,
                                 **_get_base_dict())
    evaluator.iterative_fit()
    signal.signal(15, empty_signal_handler)
    evaluator.finish_up()

コード例 #4

def make_mode_holdout(data, seed, configuration, num_run, output_dir):
    global evaluator
    evaluator = HoldoutEvaluator(data,
                                 output_dir,
                                 configuration,
                                 seed=seed,
                                 num_run=num_run,
                                 all_scoring_functions=False,
                                 **_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)

コード例 #5

def make_mode_holdout_iterative_fit(data, seed, configuration, num_run,
                                    output_dir):
    global evaluator
    evaluator = HoldoutEvaluator(data,
                                 output_dir,
                                 configuration,
                                 seed=seed,
                                 num_run=num_run,
                                 all_scoring_functions=False,
                                 **_get_base_dict())
    evaluator.iterative_fit()
    signal.signal(15, empty_signal_handler)
    evaluator.finish_up()

コード例 #6

def make_mode_holdout_iterative_fit(data, seed, configuration, num_run):
    global evaluator
    evaluator = HoldoutEvaluator(data,
                                 configuration,
                                 seed=seed,
                                 num_run=num_run,
                                 **_get_base_dict())
    evaluator.iterative_fit()
    signal.signal(15, empty_signal_handler)
    evaluator.finish_up()

    backend = Backend(None, os.getcwd())
    if os.path.exists(backend.get_model_dir()):
        backend.save_model(evaluator.model, num_run, seed)