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    <title>topic Intel Python: sklearn test output  in Intel® Distribution for Python*</title>
    <link>https://community.intel.com/t5/Intel-Distribution-for-Python/Intel-Python-sklearn-test-output/m-p/1085685#M312</link>
    <description>&lt;P&gt;&amp;nbsp;&lt;/P&gt;

&lt;P&gt;Just for your information, below is the output of:&lt;/P&gt;

&lt;PRE class="brush:python;"&gt;nosetests -v sklearn&lt;/PRE&gt;

&lt;P&gt;Sergio&lt;BR /&gt;
	&lt;STRONG&gt;Enhance your #MachineLearning and #BigData skills via #Python #SciPy:&lt;/STRONG&gt;&lt;BR /&gt;
	1) &lt;A href="https://www.packtpub.com/big-data-and-business-intelligence/numerical-and-scientific-computing-scipy-video"&gt;https://www.packtpub.com/big-data-and-business-intelligence/numerical-and-scientific-computing-scipy-video&lt;/A&gt;&lt;BR /&gt;
	2) &lt;A href="https://www.packtpub.com/big-data-and-business-intelligence/learning-scipy-numerical-and-scientific-computing-second-edition"&gt;https://www.packtpub.com/big-data-and-business-intelligence/learning-scipy-numerical-and-scientific-computing-second-edition&lt;/A&gt;&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	ERROR: /home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_c&lt;BR /&gt;
	ommon.py.test_non_meta_estimators:check_estimators_pickle(LinearRegression)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 830, in __call__&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.check(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 355, in wrapper&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return fn(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/estim&lt;BR /&gt;
	ator_checks.py", line 889, in check_estimators_pickle&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; pickled_estimator = pickle.dumps(estimator)&lt;BR /&gt;
	TypeError: can't pickle SwigPyObject objects&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	ERROR: /home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_c&lt;BR /&gt;
	ommon.py.test_non_meta_estimators:check_fit2d_predict1d(LinearRegression)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 830, in __call__&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.check(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/estim&lt;BR /&gt;
	ator_checks.py", line 479, in check_fit2d_predict1d&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; getattr(estimator, method), X[0])&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 186, in assert_warns&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; result = func(*args, **kw)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/daal4sklear&lt;BR /&gt;
	n/linear.py", line 156, in predict&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return daal_predict(self, X)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/daal4sklear&lt;BR /&gt;
	n/linear.py", line 56, in daal_predict&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; predictionResult = algorithm.compute()&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/daal/algorithms/lin&lt;BR /&gt;
	ear_regression/prediction.py", line 253, in compute&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return _prediction9.Batch_Float64DefaultDense_compute(self)&lt;BR /&gt;
	SystemError: Number of columns in numeric table is incorrect&lt;BR /&gt;
	Details:&lt;BR /&gt;
	Argument name: beta&lt;/P&gt;

&lt;P&gt;&lt;BR /&gt;
	======================================================================&lt;BR /&gt;
	ERROR: /home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_c&lt;BR /&gt;
	ommon.py.test_non_meta_estimators:check_estimators_pickle(RANSACRegressor)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 830, in __call__&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.check(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 355, in wrapper&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return fn(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/estim&lt;BR /&gt;
	ator_checks.py", line 889, in check_estimators_pickle&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; pickled_estimator = pickle.dumps(estimator)&lt;BR /&gt;
	TypeError: can't pickle SwigPyObject objects&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	ERROR: /home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_c&lt;BR /&gt;
	ommon.py.test_non_meta_estimators:check_supervised_y_2d(RANSACRegressor)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 830, in __call__&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.check(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 355, in wrapper&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return fn(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/estim&lt;BR /&gt;
	ator_checks.py", line 1151, in check_supervised_y_2d&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; estimator.fit(X, y[:, np.newaxis])&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/linear_mode&lt;BR /&gt;
	l/ransac.py", line 363, in fit&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.residual_threshold))&lt;BR /&gt;
	ValueError: No inliers found, possible cause is setting residual_threshold (None&lt;BR /&gt;
	) too low.&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	ERROR: /home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_c&lt;BR /&gt;
	ommon.py.test_non_meta_estimators:check_fit2d_predict1d(RANSACRegressor)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 830, in __call__&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.check(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/estim&lt;BR /&gt;
	ator_checks.py", line 479, in check_fit2d_predict1d&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; getattr(estimator, method), X[0])&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 186, in assert_warns&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; result = func(*args, **kw)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/linear_mode&lt;BR /&gt;
	l/ransac.py", line 428, in predict&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.estimator_.predict(X)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/daal4sklear&lt;BR /&gt;
	n/linear.py", line 156, in predict&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return daal_predict(self, X)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/daal4sklear&lt;BR /&gt;
	n/linear.py", line 56, in daal_predict&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; predictionResult = algorithm.compute()&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/daal/algorithms/lin&lt;BR /&gt;
	ear_regression/prediction.py", line 253, in compute&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return _prediction9.Batch_Float64DefaultDense_compute(self)&lt;BR /&gt;
	SystemError: Number of columns in numeric table is incorrect&lt;BR /&gt;
	Details:&lt;BR /&gt;
	Argument name: beta&lt;/P&gt;

&lt;P&gt;&lt;BR /&gt;
	======================================================================&lt;BR /&gt;
	ERROR: /home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_c&lt;BR /&gt;
	ommon.py.test_non_meta_estimators:check_estimators_pickle(Ridge)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 830, in __call__&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.check(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 355, in wrapper&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return fn(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/estim&lt;BR /&gt;
	ator_checks.py", line 889, in check_estimators_pickle&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; pickled_estimator = pickle.dumps(estimator)&lt;BR /&gt;
	TypeError: can't pickle SwigPyObject objects&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: sklearn.cluster.tests.test_bicluster.test_project_and_cluster&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/cluster/tes&lt;BR /&gt;
	ts/test_bicluster.py", line 207, in test_project_and_cluster&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; assert_array_equal(labels, [0, 0, 1, 1])&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 813, in assert_array_equal&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; verbose=verbose, header='Arrays are not equal')&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 739, in assert_array_compare&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; raise AssertionError(msg)&lt;BR /&gt;
	AssertionError:&lt;BR /&gt;
	Arrays are not equal&lt;/P&gt;

&lt;P&gt;(mismatch 100.0%)&lt;BR /&gt;
	&amp;nbsp;x: array([1, 1, 0, 0], dtype=int32)&lt;BR /&gt;
	&amp;nbsp;y: array([0, 0, 1, 1])&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: sklearn.cluster.tests.test_k_means.test_k_means_non_collapsed&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/cluster/tes&lt;BR /&gt;
	ts/test_k_means.py", line 552, in test_k_means_non_collapsed&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; assert_equal(len(np.unique(km.labels_)), 3)&lt;BR /&gt;
	AssertionError: 1 != 3&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: sklearn.linear_model.tests.test_ridge.test_dense_sparse(&amp;lt;function _test_ri&lt;BR /&gt;
	dge_loo at 0x7fb59bd21840&amp;gt;,)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/linear_mode&lt;BR /&gt;
	l/tests/test_ridge.py", line 454, in check_dense_sparse&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; ret_dense = test_func(DENSE_FILTER)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/linear_mode&lt;BR /&gt;
	l/tests/test_ridge.py", line 329, in _test_ridge_loo&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; assert_almost_equal(errors, errors2)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 523, in assert_almost_equal&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return assert_array_almost_equal(actual, desired, decimal, err_msg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 918, in assert_array_almost_equal&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; precision=decimal)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 739, in assert_array_compare&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; raise AssertionError(msg)&lt;BR /&gt;
	AssertionError:&lt;BR /&gt;
	Arrays are not almost equal to 7 decimals&lt;/P&gt;

&lt;P&gt;(mismatch 100.0%)&lt;BR /&gt;
	&amp;nbsp;x: array([&amp;nbsp; 1.8295168e+04,&amp;nbsp;&amp;nbsp; 5.6704414e+02,&amp;nbsp;&amp;nbsp; 1.1782287e+03,&amp;nbsp;&amp;nbsp; 5.2810053e+03,&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 3.8443835e+02,&amp;nbsp;&amp;nbsp; 8.0439421e+03,&amp;nbsp;&amp;nbsp; 2.3982367e+03,&amp;nbsp;&amp;nbsp; 3.3362619e+03,&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1.1783452e+01,&amp;nbsp;&amp;nbsp; 5.1091672e+03,&amp;nbsp;&amp;nbsp; 1.3139571e+04,&amp;nbsp;&amp;nbsp; 1.5552388e+01,...&lt;BR /&gt;
	&amp;nbsp;y: array([&amp;nbsp; 1.8505354e+04,&amp;nbsp;&amp;nbsp; 6.0452467e+02,&amp;nbsp;&amp;nbsp; 1.1257434e+03,&amp;nbsp;&amp;nbsp; 5.1693552e+03,&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 4.1556914e+02,&amp;nbsp;&amp;nbsp; 8.1834151e+03,&amp;nbsp;&amp;nbsp; 2.4742189e+03,&amp;nbsp;&amp;nbsp; 3.4259267e+03,&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1.7722638e+01,&amp;nbsp;&amp;nbsp; 4.9988370e+03,&amp;nbsp;&amp;nbsp; 1.3318625e+04,&amp;nbsp;&amp;nbsp; 1.0045693e+01,...&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: sklearn.manifold.tests.test_spectral_embedding.test_pipeline_spectral_clus&lt;BR /&gt;
	tering&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/manifold/te&lt;BR /&gt;
	sts/test_spectral_embedding.py", line 198, in test_pipeline_spectral_clustering&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; true_labels), 1.0, 2)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 918, in assert_array_almost_equal&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; precision=decimal)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 739, in assert_array_compare&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; raise AssertionError(msg)&lt;BR /&gt;
	AssertionError:&lt;BR /&gt;
	Arrays are not almost equal to 2 decimals&lt;/P&gt;

&lt;P&gt;(mismatch 100.0%)&lt;BR /&gt;
	&amp;nbsp;x: array(0.5866188259941206)&lt;BR /&gt;
	&amp;nbsp;y: array(1.0)&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: sklearn.mixture.tests.test_dpgmm.test_class_weights&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 355, in wrapper&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return fn(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/mixture/tes&lt;BR /&gt;
	ts/test_dpgmm.py", line 41, in test_class_weights&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; assert_array_less(dpgmm.weights_[~active], .05)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 990, in assert_array_less&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; header='Arrays are not less-ordered')&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 739, in assert_array_compare&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; raise AssertionError(msg)&lt;BR /&gt;
	AssertionError:&lt;BR /&gt;
	Arrays are not less-ordered&lt;/P&gt;

&lt;P&gt;(mismatch 14.285714285714292%)&lt;BR /&gt;
	&amp;nbsp;x: array([ 0.227048,&amp;nbsp; 0.035354,&amp;nbsp; 0.034998,&amp;nbsp; 0.03491 ,&amp;nbsp; 0.034875,&amp;nbsp; 0.034874,&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 0.034887])&lt;BR /&gt;
	&amp;nbsp;y: array(0.05)&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: sklearn.model_selection.tests.test_validation.test_cross_val_score_with_sc&lt;BR /&gt;
	ore_func_regression&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/model_selec&lt;BR /&gt;
	tion/tests/test_validation.py", line 418, in test_cross_val_score_with_score_fun&lt;BR /&gt;
	c_regression&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; assert_array_almost_equal(neg_mse_scores, expected_neg_mse, 2)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 918, in assert_array_almost_equal&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; precision=decimal)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 739, in assert_array_compare&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; raise AssertionError(msg)&lt;BR /&gt;
	AssertionError:&lt;BR /&gt;
	Arrays are not almost equal to 2 decimals&lt;/P&gt;

&lt;P&gt;(mismatch 100.0%)&lt;BR /&gt;
	&amp;nbsp;x: array([ -760.52,&amp;nbsp; -514.85,&amp;nbsp; -265.83,&amp;nbsp; -275.24, -1647.&amp;nbsp; ])&lt;BR /&gt;
	&amp;nbsp;y: array([ -763.07,&amp;nbsp; -553.16,&amp;nbsp; -274.38,&amp;nbsp; -273.26, -1681.99])&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: /home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_co&lt;BR /&gt;
	mmon.py.test_non_meta_estimators:check_estimators_nan_inf(LinearRegression)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 830, in __call__&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.check(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/estim&lt;BR /&gt;
	ator_checks.py", line 840, in check_estimators_nan_inf&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; raise AssertionError(error_string_predict, Estimator)&lt;BR /&gt;
	AssertionError: ("Estimator doesn't check for NaN and inf in predict.", &amp;lt;class '&lt;BR /&gt;
	sklearn.linear_model.base.LinearRegression'&amp;gt;)&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: /home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_co&lt;BR /&gt;
	mmon.py.test_non_meta_estimators:check_estimators_nan_inf(RANSACRegressor)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 830, in __call__&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.check(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/estim&lt;BR /&gt;
	ator_checks.py", line 840, in check_estimators_nan_inf&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; raise AssertionError(error_string_predict, Estimator)&lt;BR /&gt;
	AssertionError: ("Estimator doesn't check for NaN and inf in predict.", &amp;lt;class '&lt;BR /&gt;
	sklearn.linear_model.ransac.RANSACRegressor'&amp;gt;)&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: sklearn.tests.test_cross_validation.test_cross_val_score_with_score_func_r&lt;BR /&gt;
	egression&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_&lt;BR /&gt;
	cross_validation.py", line 918, in test_cross_val_score_with_score_func_regressi&lt;BR /&gt;
	on&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; assert_array_almost_equal(neg_mse_scores, expected_neg_mse, 2)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 918, in assert_array_almost_equal&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; precision=decimal)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 739, in assert_array_compare&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; raise AssertionError(msg)&lt;BR /&gt;
	AssertionError:&lt;BR /&gt;
	Arrays are not almost equal to 2 decimals&lt;/P&gt;

&lt;P&gt;(mismatch 100.0%)&lt;BR /&gt;
	&amp;nbsp;x: array([ -760.52,&amp;nbsp; -514.85,&amp;nbsp; -265.83,&amp;nbsp; -275.24, -1647.&amp;nbsp; ])&lt;BR /&gt;
	&amp;nbsp;y: array([ -763.07,&amp;nbsp; -553.16,&amp;nbsp; -274.38,&amp;nbsp; -273.26, -1681.99])&lt;/P&gt;

&lt;P&gt;----------------------------------------------------------------------&lt;BR /&gt;
	Ran 7166 tests in 203.755s&lt;/P&gt;

&lt;P&gt;FAILED (SKIP=14, errors=6, failures=9)&lt;/P&gt;</description>
    <pubDate>Sun, 16 Apr 2017 21:42:23 GMT</pubDate>
    <dc:creator>sergio_r_</dc:creator>
    <dc:date>2017-04-16T21:42:23Z</dc:date>
    <item>
      <title>Intel Python: sklearn test output</title>
      <link>https://community.intel.com/t5/Intel-Distribution-for-Python/Intel-Python-sklearn-test-output/m-p/1085685#M312</link>
      <description>&lt;P&gt;&amp;nbsp;&lt;/P&gt;

&lt;P&gt;Just for your information, below is the output of:&lt;/P&gt;

&lt;PRE class="brush:python;"&gt;nosetests -v sklearn&lt;/PRE&gt;

&lt;P&gt;Sergio&lt;BR /&gt;
	&lt;STRONG&gt;Enhance your #MachineLearning and #BigData skills via #Python #SciPy:&lt;/STRONG&gt;&lt;BR /&gt;
	1) &lt;A href="https://www.packtpub.com/big-data-and-business-intelligence/numerical-and-scientific-computing-scipy-video"&gt;https://www.packtpub.com/big-data-and-business-intelligence/numerical-and-scientific-computing-scipy-video&lt;/A&gt;&lt;BR /&gt;
	2) &lt;A href="https://www.packtpub.com/big-data-and-business-intelligence/learning-scipy-numerical-and-scientific-computing-second-edition"&gt;https://www.packtpub.com/big-data-and-business-intelligence/learning-scipy-numerical-and-scientific-computing-second-edition&lt;/A&gt;&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	ERROR: /home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_c&lt;BR /&gt;
	ommon.py.test_non_meta_estimators:check_estimators_pickle(LinearRegression)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 830, in __call__&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.check(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 355, in wrapper&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return fn(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/estim&lt;BR /&gt;
	ator_checks.py", line 889, in check_estimators_pickle&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; pickled_estimator = pickle.dumps(estimator)&lt;BR /&gt;
	TypeError: can't pickle SwigPyObject objects&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	ERROR: /home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_c&lt;BR /&gt;
	ommon.py.test_non_meta_estimators:check_fit2d_predict1d(LinearRegression)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 830, in __call__&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.check(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/estim&lt;BR /&gt;
	ator_checks.py", line 479, in check_fit2d_predict1d&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; getattr(estimator, method), X[0])&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 186, in assert_warns&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; result = func(*args, **kw)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/daal4sklear&lt;BR /&gt;
	n/linear.py", line 156, in predict&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return daal_predict(self, X)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/daal4sklear&lt;BR /&gt;
	n/linear.py", line 56, in daal_predict&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; predictionResult = algorithm.compute()&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/daal/algorithms/lin&lt;BR /&gt;
	ear_regression/prediction.py", line 253, in compute&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return _prediction9.Batch_Float64DefaultDense_compute(self)&lt;BR /&gt;
	SystemError: Number of columns in numeric table is incorrect&lt;BR /&gt;
	Details:&lt;BR /&gt;
	Argument name: beta&lt;/P&gt;

&lt;P&gt;&lt;BR /&gt;
	======================================================================&lt;BR /&gt;
	ERROR: /home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_c&lt;BR /&gt;
	ommon.py.test_non_meta_estimators:check_estimators_pickle(RANSACRegressor)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 830, in __call__&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.check(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 355, in wrapper&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return fn(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/estim&lt;BR /&gt;
	ator_checks.py", line 889, in check_estimators_pickle&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; pickled_estimator = pickle.dumps(estimator)&lt;BR /&gt;
	TypeError: can't pickle SwigPyObject objects&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	ERROR: /home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_c&lt;BR /&gt;
	ommon.py.test_non_meta_estimators:check_supervised_y_2d(RANSACRegressor)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 830, in __call__&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.check(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 355, in wrapper&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return fn(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/estim&lt;BR /&gt;
	ator_checks.py", line 1151, in check_supervised_y_2d&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; estimator.fit(X, y[:, np.newaxis])&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/linear_mode&lt;BR /&gt;
	l/ransac.py", line 363, in fit&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.residual_threshold))&lt;BR /&gt;
	ValueError: No inliers found, possible cause is setting residual_threshold (None&lt;BR /&gt;
	) too low.&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	ERROR: /home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_c&lt;BR /&gt;
	ommon.py.test_non_meta_estimators:check_fit2d_predict1d(RANSACRegressor)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 830, in __call__&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.check(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/estim&lt;BR /&gt;
	ator_checks.py", line 479, in check_fit2d_predict1d&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; getattr(estimator, method), X[0])&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 186, in assert_warns&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; result = func(*args, **kw)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/linear_mode&lt;BR /&gt;
	l/ransac.py", line 428, in predict&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.estimator_.predict(X)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/daal4sklear&lt;BR /&gt;
	n/linear.py", line 156, in predict&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return daal_predict(self, X)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/daal4sklear&lt;BR /&gt;
	n/linear.py", line 56, in daal_predict&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; predictionResult = algorithm.compute()&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/daal/algorithms/lin&lt;BR /&gt;
	ear_regression/prediction.py", line 253, in compute&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return _prediction9.Batch_Float64DefaultDense_compute(self)&lt;BR /&gt;
	SystemError: Number of columns in numeric table is incorrect&lt;BR /&gt;
	Details:&lt;BR /&gt;
	Argument name: beta&lt;/P&gt;

&lt;P&gt;&lt;BR /&gt;
	======================================================================&lt;BR /&gt;
	ERROR: /home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_c&lt;BR /&gt;
	ommon.py.test_non_meta_estimators:check_estimators_pickle(Ridge)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 830, in __call__&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.check(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 355, in wrapper&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return fn(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/estim&lt;BR /&gt;
	ator_checks.py", line 889, in check_estimators_pickle&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; pickled_estimator = pickle.dumps(estimator)&lt;BR /&gt;
	TypeError: can't pickle SwigPyObject objects&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: sklearn.cluster.tests.test_bicluster.test_project_and_cluster&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/cluster/tes&lt;BR /&gt;
	ts/test_bicluster.py", line 207, in test_project_and_cluster&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; assert_array_equal(labels, [0, 0, 1, 1])&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 813, in assert_array_equal&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; verbose=verbose, header='Arrays are not equal')&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 739, in assert_array_compare&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; raise AssertionError(msg)&lt;BR /&gt;
	AssertionError:&lt;BR /&gt;
	Arrays are not equal&lt;/P&gt;

&lt;P&gt;(mismatch 100.0%)&lt;BR /&gt;
	&amp;nbsp;x: array([1, 1, 0, 0], dtype=int32)&lt;BR /&gt;
	&amp;nbsp;y: array([0, 0, 1, 1])&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: sklearn.cluster.tests.test_k_means.test_k_means_non_collapsed&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/cluster/tes&lt;BR /&gt;
	ts/test_k_means.py", line 552, in test_k_means_non_collapsed&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; assert_equal(len(np.unique(km.labels_)), 3)&lt;BR /&gt;
	AssertionError: 1 != 3&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: sklearn.linear_model.tests.test_ridge.test_dense_sparse(&amp;lt;function _test_ri&lt;BR /&gt;
	dge_loo at 0x7fb59bd21840&amp;gt;,)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/linear_mode&lt;BR /&gt;
	l/tests/test_ridge.py", line 454, in check_dense_sparse&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; ret_dense = test_func(DENSE_FILTER)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/linear_mode&lt;BR /&gt;
	l/tests/test_ridge.py", line 329, in _test_ridge_loo&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; assert_almost_equal(errors, errors2)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 523, in assert_almost_equal&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return assert_array_almost_equal(actual, desired, decimal, err_msg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 918, in assert_array_almost_equal&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; precision=decimal)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 739, in assert_array_compare&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; raise AssertionError(msg)&lt;BR /&gt;
	AssertionError:&lt;BR /&gt;
	Arrays are not almost equal to 7 decimals&lt;/P&gt;

&lt;P&gt;(mismatch 100.0%)&lt;BR /&gt;
	&amp;nbsp;x: array([&amp;nbsp; 1.8295168e+04,&amp;nbsp;&amp;nbsp; 5.6704414e+02,&amp;nbsp;&amp;nbsp; 1.1782287e+03,&amp;nbsp;&amp;nbsp; 5.2810053e+03,&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 3.8443835e+02,&amp;nbsp;&amp;nbsp; 8.0439421e+03,&amp;nbsp;&amp;nbsp; 2.3982367e+03,&amp;nbsp;&amp;nbsp; 3.3362619e+03,&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1.1783452e+01,&amp;nbsp;&amp;nbsp; 5.1091672e+03,&amp;nbsp;&amp;nbsp; 1.3139571e+04,&amp;nbsp;&amp;nbsp; 1.5552388e+01,...&lt;BR /&gt;
	&amp;nbsp;y: array([&amp;nbsp; 1.8505354e+04,&amp;nbsp;&amp;nbsp; 6.0452467e+02,&amp;nbsp;&amp;nbsp; 1.1257434e+03,&amp;nbsp;&amp;nbsp; 5.1693552e+03,&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 4.1556914e+02,&amp;nbsp;&amp;nbsp; 8.1834151e+03,&amp;nbsp;&amp;nbsp; 2.4742189e+03,&amp;nbsp;&amp;nbsp; 3.4259267e+03,&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 1.7722638e+01,&amp;nbsp;&amp;nbsp; 4.9988370e+03,&amp;nbsp;&amp;nbsp; 1.3318625e+04,&amp;nbsp;&amp;nbsp; 1.0045693e+01,...&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: sklearn.manifold.tests.test_spectral_embedding.test_pipeline_spectral_clus&lt;BR /&gt;
	tering&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/manifold/te&lt;BR /&gt;
	sts/test_spectral_embedding.py", line 198, in test_pipeline_spectral_clustering&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; true_labels), 1.0, 2)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 918, in assert_array_almost_equal&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; precision=decimal)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 739, in assert_array_compare&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; raise AssertionError(msg)&lt;BR /&gt;
	AssertionError:&lt;BR /&gt;
	Arrays are not almost equal to 2 decimals&lt;/P&gt;

&lt;P&gt;(mismatch 100.0%)&lt;BR /&gt;
	&amp;nbsp;x: array(0.5866188259941206)&lt;BR /&gt;
	&amp;nbsp;y: array(1.0)&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: sklearn.mixture.tests.test_dpgmm.test_class_weights&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 355, in wrapper&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return fn(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/mixture/tes&lt;BR /&gt;
	ts/test_dpgmm.py", line 41, in test_class_weights&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; assert_array_less(dpgmm.weights_[~active], .05)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 990, in assert_array_less&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; header='Arrays are not less-ordered')&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 739, in assert_array_compare&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; raise AssertionError(msg)&lt;BR /&gt;
	AssertionError:&lt;BR /&gt;
	Arrays are not less-ordered&lt;/P&gt;

&lt;P&gt;(mismatch 14.285714285714292%)&lt;BR /&gt;
	&amp;nbsp;x: array([ 0.227048,&amp;nbsp; 0.035354,&amp;nbsp; 0.034998,&amp;nbsp; 0.03491 ,&amp;nbsp; 0.034875,&amp;nbsp; 0.034874,&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; 0.034887])&lt;BR /&gt;
	&amp;nbsp;y: array(0.05)&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: sklearn.model_selection.tests.test_validation.test_cross_val_score_with_sc&lt;BR /&gt;
	ore_func_regression&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/model_selec&lt;BR /&gt;
	tion/tests/test_validation.py", line 418, in test_cross_val_score_with_score_fun&lt;BR /&gt;
	c_regression&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; assert_array_almost_equal(neg_mse_scores, expected_neg_mse, 2)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 918, in assert_array_almost_equal&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; precision=decimal)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 739, in assert_array_compare&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; raise AssertionError(msg)&lt;BR /&gt;
	AssertionError:&lt;BR /&gt;
	Arrays are not almost equal to 2 decimals&lt;/P&gt;

&lt;P&gt;(mismatch 100.0%)&lt;BR /&gt;
	&amp;nbsp;x: array([ -760.52,&amp;nbsp; -514.85,&amp;nbsp; -265.83,&amp;nbsp; -275.24, -1647.&amp;nbsp; ])&lt;BR /&gt;
	&amp;nbsp;y: array([ -763.07,&amp;nbsp; -553.16,&amp;nbsp; -274.38,&amp;nbsp; -273.26, -1681.99])&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: /home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_co&lt;BR /&gt;
	mmon.py.test_non_meta_estimators:check_estimators_nan_inf(LinearRegression)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 830, in __call__&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.check(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/estim&lt;BR /&gt;
	ator_checks.py", line 840, in check_estimators_nan_inf&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; raise AssertionError(error_string_predict, Estimator)&lt;BR /&gt;
	AssertionError: ("Estimator doesn't check for NaN and inf in predict.", &amp;lt;class '&lt;BR /&gt;
	sklearn.linear_model.base.LinearRegression'&amp;gt;)&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: /home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_co&lt;BR /&gt;
	mmon.py.test_non_meta_estimators:check_estimators_nan_inf(RANSACRegressor)&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/testi&lt;BR /&gt;
	ng.py", line 830, in __call__&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; return self.check(*args, **kwargs)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/utils/estim&lt;BR /&gt;
	ator_checks.py", line 840, in check_estimators_nan_inf&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; raise AssertionError(error_string_predict, Estimator)&lt;BR /&gt;
	AssertionError: ("Estimator doesn't check for NaN and inf in predict.", &amp;lt;class '&lt;BR /&gt;
	sklearn.linear_model.ransac.RANSACRegressor'&amp;gt;)&lt;/P&gt;

&lt;P&gt;======================================================================&lt;BR /&gt;
	FAIL: sklearn.tests.test_cross_validation.test_cross_val_score_with_score_func_r&lt;BR /&gt;
	egression&lt;BR /&gt;
	----------------------------------------------------------------------&lt;BR /&gt;
	Traceback (most recent call last):&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/nose/case.py", line&lt;BR /&gt;
	&amp;nbsp;198, in runTest&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; self.test(*self.arg)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/sklearn/tests/test_&lt;BR /&gt;
	cross_validation.py", line 918, in test_cross_val_score_with_score_func_regressi&lt;BR /&gt;
	on&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; assert_array_almost_equal(neg_mse_scores, expected_neg_mse, 2)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 918, in assert_array_almost_equal&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; precision=decimal)&lt;BR /&gt;
	&amp;nbsp; File "/home/intel/intelpython3/lib/python3.5/site-packages/numpy/testing/utils&lt;BR /&gt;
	.py", line 739, in assert_array_compare&lt;BR /&gt;
	&amp;nbsp;&amp;nbsp;&amp;nbsp; raise AssertionError(msg)&lt;BR /&gt;
	AssertionError:&lt;BR /&gt;
	Arrays are not almost equal to 2 decimals&lt;/P&gt;

&lt;P&gt;(mismatch 100.0%)&lt;BR /&gt;
	&amp;nbsp;x: array([ -760.52,&amp;nbsp; -514.85,&amp;nbsp; -265.83,&amp;nbsp; -275.24, -1647.&amp;nbsp; ])&lt;BR /&gt;
	&amp;nbsp;y: array([ -763.07,&amp;nbsp; -553.16,&amp;nbsp; -274.38,&amp;nbsp; -273.26, -1681.99])&lt;/P&gt;

&lt;P&gt;----------------------------------------------------------------------&lt;BR /&gt;
	Ran 7166 tests in 203.755s&lt;/P&gt;

&lt;P&gt;FAILED (SKIP=14, errors=6, failures=9)&lt;/P&gt;</description>
      <pubDate>Sun, 16 Apr 2017 21:42:23 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-Distribution-for-Python/Intel-Python-sklearn-test-output/m-p/1085685#M312</guid>
      <dc:creator>sergio_r_</dc:creator>
      <dc:date>2017-04-16T21:42:23Z</dc:date>
    </item>
    <item>
      <title>Hi Sergio,</title>
      <link>https://community.intel.com/t5/Intel-Distribution-for-Python/Intel-Python-sklearn-test-output/m-p/1085686#M313</link>
      <description>&lt;P&gt;Hi Sergio,&lt;/P&gt;

&lt;P&gt;I assume you executed the tests on Linux or on macOS. Instead of providing relevant information for your thread, it seems you focused on promoting your video and your book published by Packt. I've published ten books with Packt and I never needed to SPAM in forums to get attention. In fact, it is not a good practice at all. You will be flagged as SPAM and probably, your threads or posts won't be considered as serious threads or posts in the communities or forums. Take a look at the threads opened in these forums and you will notice that most professionals provide a detailed description of the problem.&lt;/P&gt;

&lt;P&gt;I assume you didn't open this new thread just to SPAM and that you wanted to share the results of executing the tests with Intel Distribution for Python.&lt;/P&gt;

&lt;P&gt;Let me share the results of running the same tests on Intel Distribution for Python 3.5.2 on Windows 10 64-bits:&lt;/P&gt;

&lt;PRE class="brush:plain;"&gt;======================================================================
ERROR: C:\IntelPython35\lib\site-packages\sklearn\tests\test_common.py.test_non_meta_estimators:check_estimators_pickle(LinearRegression)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\IntelPython35\lib\site-packages\nose\case.py", line 198, in runTest
    self.test(*self.arg)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\testing.py", line 830, in __call__
    return self.check(*args, **kwargs)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\testing.py", line 355, in wrapper
    return fn(*args, **kwargs)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\estimator_checks.py", line 889, in check_estimators_pickle
    pickled_estimator = pickle.dumps(estimator)
TypeError: can't pickle SwigPyObject objects

======================================================================
ERROR: C:\IntelPython35\lib\site-packages\sklearn\tests\test_common.py.test_non_meta_estimators:check_fit2d_predict1d(LinearRegression)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\IntelPython35\lib\site-packages\nose\case.py", line 198, in runTest
    self.test(*self.arg)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\testing.py", line 830, in __call__
    return self.check(*args, **kwargs)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\estimator_checks.py", line 479, in check_fit2d_predict1d
    getattr(estimator, method), X[0])
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\testing.py", line 186, in assert_warns
    result = func(*args, **kw)
  File "C:\IntelPython35\lib\site-packages\sklearn\daal4sklearn\linear.py", line 155, in predict
    return daal_predict(self, X)
  File "C:\IntelPython35\lib\site-packages\sklearn\daal4sklearn\linear.py", line 55, in daal_predict
    predictionResult = algorithm.compute()
  File "C:\IntelPython35\lib\site-packages\daal\algorithms\linear_regression\prediction.py", line 252, in compute
    return _prediction5.Batch_Float64DefaultDense_compute(self)
SystemError: Number of columns in numeric table is incorrect
Details:
Argument name: beta


======================================================================
ERROR: C:\IntelPython35\lib\site-packages\sklearn\tests\test_common.py.test_non_meta_estimators:check_estimators_pickle(RANSACRegressor)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\IntelPython35\lib\site-packages\nose\case.py", line 198, in runTest
    self.test(*self.arg)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\testing.py", line 830, in __call__
    return self.check(*args, **kwargs)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\testing.py", line 355, in wrapper
    return fn(*args, **kwargs)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\estimator_checks.py", line 889, in check_estimators_pickle
    pickled_estimator = pickle.dumps(estimator)
TypeError: can't pickle SwigPyObject objects

======================================================================
ERROR: C:\IntelPython35\lib\site-packages\sklearn\tests\test_common.py.test_non_meta_estimators:check_supervised_y_2d(RANSACRegressor)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\IntelPython35\lib\site-packages\nose\case.py", line 198, in runTest
    self.test(*self.arg)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\testing.py", line 830, in __call__
    return self.check(*args, **kwargs)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\testing.py", line 355, in wrapper
    return fn(*args, **kwargs)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\estimator_checks.py", line 1151, in check_supervised_y_2d
    estimator.fit(X, y[:, np.newaxis])
  File "C:\IntelPython35\lib\site-packages\sklearn\linear_model\ransac.py", line 363, in fit
    self.residual_threshold))
ValueError: No inliers found, possible cause is setting residual_threshold (None) too low.

======================================================================
ERROR: C:\IntelPython35\lib\site-packages\sklearn\tests\test_common.py.test_non_meta_estimators:check_fit2d_predict1d(RANSACRegressor)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\IntelPython35\lib\site-packages\nose\case.py", line 198, in runTest
    self.test(*self.arg)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\testing.py", line 830, in __call__
    return self.check(*args, **kwargs)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\estimator_checks.py", line 479, in check_fit2d_predict1d
    getattr(estimator, method), X[0])
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\testing.py", line 186, in assert_warns
    result = func(*args, **kw)
  File "C:\IntelPython35\lib\site-packages\sklearn\linear_model\ransac.py", line 428, in predict
    return self.estimator_.predict(X)
  File "C:\IntelPython35\lib\site-packages\sklearn\daal4sklearn\linear.py", line 155, in predict
    return daal_predict(self, X)
  File "C:\IntelPython35\lib\site-packages\sklearn\daal4sklearn\linear.py", line 55, in daal_predict
    predictionResult = algorithm.compute()
  File "C:\IntelPython35\lib\site-packages\daal\algorithms\linear_regression\prediction.py", line 252, in compute
    return _prediction5.Batch_Float64DefaultDense_compute(self)
SystemError: Number of columns in numeric table is incorrect
Details:
Argument name: beta


======================================================================
ERROR: C:\IntelPython35\lib\site-packages\sklearn\tests\test_common.py.test_non_meta_estimators:check_estimators_pickle(Ridge)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\IntelPython35\lib\site-packages\nose\case.py", line 198, in runTest
    self.test(*self.arg)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\testing.py", line 830, in __call__
    return self.check(*args, **kwargs)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\testing.py", line 355, in wrapper
    return fn(*args, **kwargs)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\estimator_checks.py", line 889, in check_estimators_pickle
    pickled_estimator = pickle.dumps(estimator)
TypeError: can't pickle SwigPyObject objects

======================================================================
FAIL: sklearn.decomposition.tests.test_fastica.test_fastica_simple
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\IntelPython35\lib\site-packages\nose\case.py", line 198, in runTest
    self.test(*self.arg)
  File "C:\IntelPython35\lib\site-packages\sklearn\decomposition\tests\test_fastica.py", line 110, in test_fastica_simple
    assert_almost_equal(np.dot(s1_, s1) / n_samples, 1, decimal=2)
  File "C:\Users\gaston\AppData\Roaming\Python\Python35\site-packages\numpy\testing\utils.py", line 589, in assert_almost_equal
    raise AssertionError(_build_err_msg())
AssertionError:
Arrays are not almost equal to 2 decimals
 ACTUAL: 0.0065581346415391354
 DESIRED: 1

======================================================================
FAIL: sklearn.linear_model.tests.test_ridge.test_dense_sparse(&amp;lt;function _test_ridge_loo at 0x0000022A0B59FC80&amp;gt;,)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\IntelPython35\lib\site-packages\nose\case.py", line 198, in runTest
    self.test(*self.arg)
  File "C:\IntelPython35\lib\site-packages\sklearn\linear_model\tests\test_ridge.py", line 454, in check_dense_sparse
    ret_dense = test_func(DENSE_FILTER)
  File "C:\IntelPython35\lib\site-packages\sklearn\linear_model\tests\test_ridge.py", line 329, in _test_ridge_loo
    assert_almost_equal(errors, errors2)
  File "C:\Users\gaston\AppData\Roaming\Python\Python35\site-packages\numpy\testing\utils.py", line 573, in assert_almost_equal
    return assert_array_almost_equal(actual, desired, decimal, err_msg)
  File "C:\Users\gaston\AppData\Roaming\Python\Python35\site-packages\numpy\testing\utils.py", line 979, in assert_array_almost_equal
    precision=decimal)
  File "C:\Users\gaston\AppData\Roaming\Python\Python35\site-packages\numpy\testing\utils.py", line 796, in assert_array_compare
    raise AssertionError(msg)
AssertionError:
Arrays are not almost equal to 7 decimals

(mismatch 100.0%)
 x: array([  1.8295168e+04,   5.6704414e+02,   1.1782287e+03,   5.2810053e+03,
         3.8443835e+02,   8.0439421e+03,   2.3982367e+03,   3.3362619e+03,
         1.1783452e+01,   5.1091672e+03,   1.3139571e+04,   1.5552388e+01,...
 y: array([  1.8505354e+04,   6.0452467e+02,   1.1257434e+03,   5.1693552e+03,
         4.1556914e+02,   8.1834151e+03,   2.4742189e+03,   3.4259267e+03,
         1.7722638e+01,   4.9988370e+03,   1.3318625e+04,   1.0045693e+01,...

======================================================================
FAIL: sklearn.model_selection.tests.test_validation.test_cross_val_score_with_score_func_regression
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\IntelPython35\lib\site-packages\nose\case.py", line 198, in runTest
    self.test(*self.arg)
  File "C:\IntelPython35\lib\site-packages\sklearn\model_selection\tests\test_validation.py", line 418, in test_cross_val_score_with_score_func_regression
    assert_array_almost_equal(neg_mse_scores, expected_neg_mse, 2)
  File "C:\Users\gaston\AppData\Roaming\Python\Python35\site-packages\numpy\testing\utils.py", line 979, in assert_array_almost_equal
    precision=decimal)
  File "C:\Users\gaston\AppData\Roaming\Python\Python35\site-packages\numpy\testing\utils.py", line 796, in assert_array_compare
    raise AssertionError(msg)
AssertionError:
Arrays are not almost equal to 2 decimals

(mismatch 100.0%)
 x: array([ -760.52,  -514.85,  -265.83,  -275.24, -1647.  ])
 y: array([ -763.07,  -553.16,  -274.38,  -273.26, -1681.99])

======================================================================
FAIL: C:\IntelPython35\lib\site-packages\sklearn\tests\test_common.py.test_non_meta_estimators:check_estimators_nan_inf(LinearRegression)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\IntelPython35\lib\site-packages\nose\case.py", line 198, in runTest
    self.test(*self.arg)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\testing.py", line 830, in __call__
    return self.check(*args, **kwargs)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\estimator_checks.py", line 840, in check_estimators_nan_inf
    raise AssertionError(error_string_predict, Estimator)
AssertionError: ("Estimator doesn't check for NaN and inf in predict.", &amp;lt;class 'sklearn.linear_model.base.LinearRegression'&amp;gt;)

======================================================================
FAIL: C:\IntelPython35\lib\site-packages\sklearn\tests\test_common.py.test_non_meta_estimators:check_estimators_nan_inf(RANSACRegressor)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\IntelPython35\lib\site-packages\nose\case.py", line 198, in runTest
    self.test(*self.arg)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\testing.py", line 830, in __call__
    return self.check(*args, **kwargs)
  File "C:\IntelPython35\lib\site-packages\sklearn\utils\estimator_checks.py", line 840, in check_estimators_nan_inf
    raise AssertionError(error_string_predict, Estimator)
AssertionError: ("Estimator doesn't check for NaN and inf in predict.", &amp;lt;class 'sklearn.linear_model.ransac.RANSACRegressor'&amp;gt;)

======================================================================
FAIL: sklearn.tests.test_cross_validation.test_cross_val_score_with_score_func_regression
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\IntelPython35\lib\site-packages\nose\case.py", line 198, in runTest
    self.test(*self.arg)
  File "C:\IntelPython35\lib\site-packages\sklearn\tests\test_cross_validation.py", line 918, in test_cross_val_score_with_score_func_regression
    assert_array_almost_equal(neg_mse_scores, expected_neg_mse, 2)
  File "C:\Users\gaston\AppData\Roaming\Python\Python35\site-packages\numpy\testing\utils.py", line 979, in assert_array_almost_equal
    precision=decimal)
  File "C:\Users\gaston\AppData\Roaming\Python\Python35\site-packages\numpy\testing\utils.py", line 796, in assert_array_compare
    raise AssertionError(msg)
AssertionError:
Arrays are not almost equal to 2 decimals

(mismatch 100.0%)
 x: array([ -760.52,  -514.85,  -265.83,  -275.24, -1647.  ])
 y: array([ -763.07,  -553.16,  -274.38,  -273.26, -1681.99])

----------------------------------------------------------------------
Ran 7159 tests in 250.648s

FAILED (SKIP=15, errors=6, failures=6)&lt;/PRE&gt;

&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 18 Apr 2017 03:02:10 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-Distribution-for-Python/Intel-Python-sklearn-test-output/m-p/1085686#M313</guid>
      <dc:creator>gaston-hillar</dc:creator>
      <dc:date>2017-04-18T03:02:10Z</dc:date>
    </item>
    <item>
      <title>This thread continued in the</title>
      <link>https://community.intel.com/t5/Intel-Distribution-for-Python/Intel-Python-sklearn-test-output/m-p/1085687#M314</link>
      <description>&lt;P&gt;This thread continued in the following thread:&amp;nbsp;&lt;A href="https://software.intel.com/en-us/forums/intel-distribution-for-python/topic/731351"&gt;https://software.intel.com/en-us/forums/intel-distribution-for-python/topic/731351&lt;/A&gt;&lt;/P&gt;</description>
      <pubDate>Wed, 19 Apr 2017 23:19:56 GMT</pubDate>
      <guid>https://community.intel.com/t5/Intel-Distribution-for-Python/Intel-Python-sklearn-test-output/m-p/1085687#M314</guid>
      <dc:creator>gaston-hillar</dc:creator>
      <dc:date>2017-04-19T23:19:56Z</dc:date>
    </item>
  </channel>
</rss>

