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empirical_covariance — scikit-learn 1.7.2 docum...
>>> X = [[ 1 , 1 , 1 ],[ 1 , 1 , 1 ],[ 1 , 1 , 1 ], ... [ 0 ,...scikit-learn.org/stable/modules/generated/sklearn.covariance.empirical_covariance.html -
OAS — scikit-learn 1.7.2 documentation
precision_ array([[ 1.7833, -1.2431 ], [-1.2431, 3.3889]]) >>>...the estimator. References [ 1 ] ( 1 , 2 ) “Shrinkage algorithms...scikit-learn.org/stable/modules/generated/sklearn.covariance.OAS.html -
BaseEstimator — scikit-learn 1.7.2 documentation
array ([ 1 , 0 , 1 ]) >>> estimator . fit ( X ,...__init__ ( self , * , param = 1 ): ... self . param = param ......scikit-learn.org/stable/modules/generated/sklearn.base.BaseEstimator.html -
Ridge — scikit-learn 1.7.2 documentation
Ridge ( alpha = 1.0 , * , fit_intercept = True ,...shape (n_targets,)}, default=1.0 Constant that multiplies the...scikit-learn.org/stable/modules/generated/sklearn.linear_model.Ridge.html -
Isomap — scikit-learn 1.7.2 documentation
Added in version 1.1. n_components int, default=2...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.manifold.Isomap.html -
pairwise_distances — scikit-learn 1.7.2 documen...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...deprecated from SciPy 1.9 and will be removed in SciPy 1.11. Note 'matching'...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise_distances.html -
lasso_path — scikit-learn 1.7.2 documentation
alpha * || w || _1 For multi-output tasks it is: ( 1 / ( 2 * n_samples...lasso_path >>> X = np . array ([[ 1 , 2 , 3.1 ], [ 2.3 , 5.4 , 4.3 ]])...scikit-learn.org/stable/modules/generated/sklearn.linear_model.lasso_path.html -
affinity_propagation — scikit-learn 1.7.2 docum...
array ([[ 1 , 2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 4 , 2...>>> labels array([0, 0, 0, 1, 1, 1]) Gallery examples # Visualizing...scikit-learn.org/stable/modules/generated/sklearn.cluster.affinity_propagation.html -
MultiOutputRegressor — scikit-learn 1.7.2 docum...
means 1 unless in a joblib.parallel_backend context. -1 means...X [[ 0 ]]) array([[176, 35.1, 57.1]]) fit ( X , y , sample_weight...scikit-learn.org/stable/modules/generated/sklearn.multioutput.MultiOutputRegressor.html -
Kernel — scikit-learn 1.7.2 documentation
length_scale = 1.0 ): ... self . length_scale =...2.0 ) >>> X = np . array ([[ 1 , 2 ], [ 3 , 4 ]]) >>> print (...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Kernel.html