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src/s/c/scikit-learn-0.14.1/sklearn/linear_model/tests/test_coordinate_descent.py   scikit-learn(Download)
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import SkipTest
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_greater
def check_warnings():
    if version_info < (2, 6):
        raise SkipTest("Testing for warnings is not supported in versions \
        older than Python 2.6")
 

src/s/c/scikit-learn-0.14.1/sklearn/datasets/tests/test_20news.py   scikit-learn(Download)
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import SkipTest
 
from sklearn import datasets
            subset='all', download_if_missing=False, shuffle=False)
    except IOError:
        raise SkipTest("Download 20 newsgroups to run this test")
 
    # Extract a reduced dataset

src/s/c/scikit-learn-0.14.1/sklearn/cluster/tests/test_k_means.py   scikit-learn(Download)
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import SkipTest
from sklearn.utils.testing import assert_almost_equal
from sklearn.utils.testing import assert_raises
def test_k_means_plus_plus_init_2_jobs():
    if _is_mac_os_version_ge('10.7'):
        raise SkipTest('Multi-process bug in Mac OS X Lion (see issue #636)')
    km = KMeans(init="k-means++", n_clusters=n_clusters, n_jobs=2,
                     random_state=42).fit(X)

src/s/c/scikit-learn-0.14.1/sklearn/linear_model/tests/test_bayes.py   scikit-learn(Download)
 
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import SkipTest
from sklearn.linear_model.bayes import BayesianRidge, ARDRegression
from sklearn import datasets
def test_bayesian_on_diabetes():
    """
    Test BayesianRidge on diabetes
    """
    raise SkipTest("XFailed Test")

src/s/c/scikit-learn-0.14.1/sklearn/decomposition/tests/test_dict_learning.py   scikit-learn(Download)
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import SkipTest
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_less

src/s/c/scikit-learn-0.14.1/sklearn/decomposition/tests/test_sparse_pca.py   scikit-learn(Download)
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import SkipTest
from sklearn.utils.testing import assert_true
from sklearn.utils.testing import assert_false

src/s/c/scikit-learn-0.14.1/sklearn/datasets/tests/test_lfw.py   scikit-learn(Download)
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import SkipTest
from sklearn.utils.testing import raises
 

src/s/c/scikit-learn-0.14.1/sklearn/datasets/tests/test_covtype.py   scikit-learn(Download)
import errno
from sklearn.datasets import fetch_covtype
from sklearn.utils.testing import assert_equal, SkipTest
 
 
    except IOError as e:
        if e.errno == errno.ENOENT:
            raise SkipTest()
 
    data2 = fetch(shuffle=True, random_state=37)