Esempi in Python per sklearn_cv_score

Esempio n. 1

File: test_dataframe_mapper.py Progetto: yonglehou/sklearn-pandas

def test_direct_cross_validation(iris_dataframe):
    """
    Starting with sklearn>=0.16.0 we no longer need CV wrappers for dataframes.
    See https://github.com/paulgb/sklearn-pandas/issues/11
    """
    pipeline = Pipeline(
        [
            (
                "preprocess",
                DataFrameMapper(
                    [
                        ("petal length (cm)", None),
                        ("petal width (cm)", None),
                        ("sepal length (cm)", None),
                        ("sepal width (cm)", None),
                    ]
                ),
            ),
            ("classify", SVC(kernel="linear")),
        ]
    )
    data = iris_dataframe.drop("species", axis=1)
    labels = iris_dataframe["species"]
    scores = sklearn_cv_score(pipeline, data, labels)
    assert scores.mean() > 0.96
    assert (scores.std() * 2) < 0.04

Esempio n. 2

File: test_dataframe_mapper.py Progetto: xulukai/sklearn-pandas

def test_direct_cross_validation(iris_dataframe):
    """
    Starting with sklearn>=0.16.0 we no longer need CV wrappers for dataframes.
    See https://github.com/paulgb/sklearn-pandas/issues/11
    """
    pipeline = Pipeline([("preprocess",
                          DataFrameMapper([
                              ("petal length (cm)", None),
                              ("petal width (cm)", None),
                              ("sepal length (cm)", None),
                              ("sepal width (cm)", None),
                          ])), ("classify", SVC(kernel='linear'))])
    data = iris_dataframe.drop("species", axis=1)
    labels = iris_dataframe["species"]
    scores = sklearn_cv_score(pipeline, data, labels)
    assert scores.mean() > 0.96
    assert (scores.std() * 2) < 0.04