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affinity_propagation — scikit-learn 1.8.0...
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 -
GroupShuffleSplit — scikit-learn 1.8.0 do...
index=[0 1], group=[1 1] Fold 1: Train: index=[0 1 5 6 7], group=[1...= ( 8 , 1 )) >>> groups = np . array ([ 1 , 1 , 2 , 2...scikit-learn.org/stable/modules/generated/sklearn.model_selection.GroupShuffleSplit.html -
FeatureHasher — scikit-learn 1.8.0 docume...
-1., 0., -1., 0., 1.], [ 0., 0., 0., -1., 0., -1., 0., 0.],...0.], [ 0., -1., 0., 0., 0., 0., 0., 1.]]) fit ( X = None , y...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.FeatureHasher.html -
compute_class_weight — scikit-learn 1.8.0...
compute_class_weight >>> y = [ 1 , 1 , 1 , 1 , 0 , 0 ] >>> ...unique ( y ), y = y ) array([1.5 , 0.75]) On this page This Page...scikit-learn.org/stable/modules/generated/sklearn.utils.class_weight.compute_class_weight.html -
NMF — scikit-learn 1.8.0 documentation
array ([[ 1 , 1 ], [ 2 , 1 ], [ 3 , 1.2 ], [ 4 , 1 ], [ 5 , 0.8...version 1.4: Added 'auto' value. Changed in version 1.6: Default...scikit-learn.org/stable/modules/generated/sklearn.decomposition.NMF.html -
ElasticNetCV — scikit-learn 1.8.0 documen...
l1_ratio = 1 it is an L1 penalty. For 0 < l1_ratio < 1 , the...(i.e. Ridge), as in [.1, .5, .7, .9, .95, .99, 1] . eps float, default=1e-3...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNetCV.html -
cluster_optics_dbscan — scikit-learn 1.8....
1, 1, 1]) Gallery examples # Demo of...>>> X = np . array ([[ 1 , 2 ], [ 2 , 5 ], [ 3 , 6 ], ......scikit-learn.org/stable/modules/generated/sklearn.cluster.cluster_optics_dbscan.html -
AgglomerativeClustering — scikit-learn 1....
array ([[ 1 , 2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 4 , 2...clustering . labels_ array([1, 1, 1, 0, 0, 0]) For a comparison...scikit-learn.org/stable/modules/generated/sklearn.cluster.AgglomerativeClustering.html -
Lasso — scikit-learn 1.8.0 documentation
1 ) >>> clf . fit ([[ 0 , 0 ], [ 1 , 1 ], [ 2...2 , 2 ]], [ 0 , 1 , 2 ]) Lasso(alpha=0.1) >>> print (...scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lasso.html -
LinearRegression — scikit-learn 1.8.0 doc...
array ([[ 1 , 1 ], [ 1 , 2 ], [ 2 , 2 ], [ 2 ,...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html