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EmpiricalCovariance — scikit-learn 1.8.0 docume...
covariance_ array([[0.7569, 0.2818], [0.2818, 0.3928]]) >>> cov ..... location_ array([0.0622, 0.0193]) error_norm ( comp_cov , norm...scikit-learn.org/stable/modules/generated/sklearn.covariance.EmpiricalCovariance.html -
get_data_home — scikit-learn 1.8.0 documentation
Gallery examples: Out-of-core classification of text documentsscikit-learn.org/stable/modules/generated/sklearn.datasets.get_data_home.html -
fetch_lfw_people — scikit-learn 1.8.0 documenta...
Added in version 1.5. delay float, default=1.0 Number of seconds...True , resize = 0.5 , min_faces_per_person = 0 , color = False...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_lfw_people.html -
MinCovDet — scikit-learn 1.8.0 documentation
0.2736], [0.2736, 0.3330]]) >>> cov . location_ array([0.0769...RandomState ( 0 ) >>> X = rng . multivariate_normal ( mean = [ 0 , 0 ],...scikit-learn.org/stable/modules/generated/sklearn.covariance.MinCovDet.html -
load_iris — scikit-learn 1.8.0 documentation
= [ 10 , 25 , 50 ] >>> data . target [ samples ] array([0, 0,...scikit-learn 0.22 Release Highlights for scikit-learn 0.22 Release...scikit-learn.org/stable/modules/generated/sklearn.datasets.load_iris.html -
make_column_transformer — scikit-learn 1.8.0 do...
means 1 unless in a joblib.parallel_backend context. -1 means...not unique. Added in version 1.0. force_int_remainder_cols bool,...scikit-learn.org/stable/modules/generated/sklearn.compose.make_column_transformer.html -
config_context — scikit-learn 1.8.0 documentation
but would print ‘SVC(C=1.0, cache_size=200, …)’ with all...configuration setting. Added in version 1.1. enable_cython_pairwise_dist...scikit-learn.org/stable/modules/generated/sklearn.config_context.html -
k_means — scikit-learn 1.8.0 documentation
array([1, 1, 1, 0, 0, 0], dtype=int32) >>> inertia 16.0 On this...([[ 1 , 2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 10 , 2 ], [ 10 , 4 ],...scikit-learn.org/stable/modules/generated/sklearn.cluster.k_means.html -
RegressorMixin — scikit-learn 1.8.0 documentation
array([0, 0, 0]) >>> estimator . score ( X , y ) 0.0 score (...]]) >>> y = np . array ([ - 1 , 0 , 1 ]) >>> estimator . fit ( X...scikit-learn.org/stable/modules/generated/sklearn.base.RegressorMixin.html -
calibration_curve — scikit-learn 1.8.0 document...
array ([ 0.1 , 0.2 , 0.3 , 0.4 , 0.65 , 0.7 , 0.8 , 0.9 , 1. ]) >>>...np . array ([ 0 , 0 , 0 , 0 , 1 , 1 , 1 , 1 , 1 ]) >>> y_pred...scikit-learn.org/stable/modules/generated/sklearn.calibration.calibration_curve.html