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DBSCAN — scikit-learn 1.8.0 documentation
labels_ array([ 0, 0, 0, 1, 1, -1]) >>> clustering DBSCAN(eps=3,...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html -
SpectralClustering — scikit-learn 1.8.0 documen...
array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7 ],...n_init = 10 , gamma = 1.0 , affinity = 'rbf' , n_neighbors = 10 , eigen_tol...scikit-learn.org/stable/modules/generated/sklearn.cluster.SpectralClustering.html -
is_regressor — scikit-learn 1.8.0 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version is_regressor # sklearn.base. is_regressor ( estimator...scikit-learn.org/stable/modules/generated/sklearn.base.is_regressor.html -
SpectralCoclustering — scikit-learn 1.8.0 docum...
array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7 ],...1, 1, 0, 0, 0], dtype=int32) >>> clustering . column_labels_ array([0,...scikit-learn.org/stable/modules/generated/sklearn.cluster.SpectralCoclustering.html -
oas — scikit-learn 1.8.0 documentation
shrunk_cov array([[0.7533, 0.2763], [0.2763, 0.3964]]) >>> shrinkage...the estimator. References [ 1 ] ( 1 , 2 ) “Shrinkage algorithms...scikit-learn.org/stable/modules/generated/oas-function.html -
LedoitWolf — scikit-learn 1.8.0 documentation
covariance_ array([[0.4406, 0.1616], [0.1616, 0.8022]]) >>> cov ..... location_ array([ 0.0595 , -0.0075]) See also Shrinkage covariance...scikit-learn.org/stable/modules/generated/sklearn.covariance.LedoitWolf.html -
GraphicalLasso — scikit-learn 1.8.0 documentation
([[ 0.8 , 0.0 , 0.2 , 0.0 ], ... [ 0.0 , 0.4 , 0.0 , 0.0 ], ......... [ 0.2 , 0.0 , 0.3 , 0.1 ], ... [ 0.0 , 0.0 , 0.1 , 0.7 ]])...scikit-learn.org/stable/modules/generated/sklearn.covariance.GraphicalLasso.html -
spectral_clustering — scikit-learn 1.8.0 docume...
random_state = 0 ... ) array([1, 1, 1, 0, 0, 0]) Gallery examples...= np . array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7 ],...scikit-learn.org/stable/modules/generated/sklearn.cluster.spectral_clustering.html -
ledoit_wolf — scikit-learn 1.8.0 documentation
array([[0.44, 0.16], [0.16, 0.80]]) >>> shrinkage np.float64(0.23)...RandomState ( 0 ) >>> X = rng . multivariate_normal ( mean = [ 0 , 0 ],...scikit-learn.org/stable/modules/generated/sklearn.covariance.ledoit_wolf.html -
ClassNamePrefixFeaturesOutMixin — scikit-learn ...
shape [ 1 ] ... return self >>> X = np . array ([[ 1 , 2 ], [...scikit-learn.org/stable/modules/generated/sklearn.base.ClassNamePrefixFeaturesOutMixin.html