Python get_non_core_objectivesの例

コード例 #1

ファイル: conftest.py プロジェクト: stjordanis/evalml

def time_series_non_core_objectives():
    non_core_time_series = [
        obj_() for obj_ in get_non_core_objectives()
        if ProblemTypes.TIME_SERIES_REGRESSION in obj_.problem_types
    ]
    return non_core_time_series

コード例 #2

ファイル: test_standard_metrics.py プロジェクト: yutiansut/evalml

from evalml.objectives import (
    F1, MAPE, MSE, AccuracyBinary, AccuracyMulticlass, BalancedAccuracyBinary,
    BalancedAccuracyMulticlass, BinaryClassificationObjective,
    CostBenefitMatrix, ExpVariance, F1Macro, F1Micro, F1Weighted,
    LogLossBinary, MCCBinary, MCCMulticlass, MeanSquaredLogError, Precision,
    PrecisionMacro, PrecisionMicro, PrecisionWeighted, Recall, RecallMacro,
    RecallMicro, RecallWeighted, RootMeanSquaredError, RootMeanSquaredLogError)
from evalml.objectives.utils import (_all_objectives_dict,
                                     get_non_core_objectives)

EPS = 1e-5
all_automl_objectives = _all_objectives_dict()
all_automl_objectives = {
    name: class_()
    for name, class_ in all_automl_objectives.items()
    if class_ not in get_non_core_objectives()
}


def test_input_contains_nan():
    y_predicted = np.array([np.nan, 0, 0])
    y_true = np.array([1, 2, 1])
    for objective in all_automl_objectives.values():
        with pytest.raises(ValueError,
                           match="y_predicted contains NaN or infinity"):
            objective.score(y_true, y_predicted)

    y_true = np.array([np.nan, 0, 0])
    y_predicted = np.array([1, 2, 0])
    for objective in all_automl_objectives.values():
        with pytest.raises(ValueError,