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make_moons — scikit-learn 1.8.0 documentation
) The integer labels (0 or 1) for class membership of each...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_moons.html -
orthogonal_mp_gram — scikit-learn 1.8.0 documen...
) >>> X [: 1 ,] @ coef array([-78.68]) On this...scikit-learn.org/stable/modules/generated/sklearn.linear_model.orthogonal_mp_gram.html -
ClassicalMDS — scikit-learn 1.8.0 documentation
scikit-learn 1.8 Release Highlights for scikit-learn 1.8 On this...non-metric MDS. References [ 1 ] “Modern Multidimensional Scaling...scikit-learn.org/stable/modules/generated/sklearn.manifold.ClassicalMDS.html -
Bunch — scikit-learn 1.8.0 documentation
import Bunch >>> b = Bunch ( a = 1 , b = 2 ) >>> b [ 'b' ] 2 >>>...scikit-learn.org/stable/modules/generated/sklearn.utils.Bunch.html -
Demo of DBSCAN clustering algorithm — scikit-le...
centers = [[ 1 , 1 ], [ - 1 , - 1 ], [ 1 , - 1 ]] X , labels_true...len ( set ( labels )) - ( 1 if - 1 in labels else 0 ) n_noise_...scikit-learn.org/stable/auto_examples/cluster/plot_dbscan.html -
Compare BIRCH and MiniBatchKMeans — scikit-lear...
threshold = 1.7 , n_clusters = None ), Birch ( threshold = 1.7 , n_clusters...= fig . add_subplot ( 1 , 3 , ind + 1 ) for this_centroid , k...scikit-learn.org/stable/auto_examples/cluster/plot_birch_vs_minibatchkmeans.html -
Inductive Clustering — scikit-learn 1.8.0 docum...
cluster_std = [ 1.0 , 1.0 , 0.5 ], centers = [( - 5.... scatter ( X [:, 0 ], X [:, 1 ], c = color , alpha = alpha ,...scikit-learn.org/stable/auto_examples/cluster/plot_inductive_clustering.html -
Metadata Routing — scikit-learn 1.8.0 documenta...
array([1., 1., 1.]) Routing Meta-Estimator...ExampleClassifier. array([1., 1., 1.]) Deprecation / Default Value...scikit-learn.org/stable/auto_examples/miscellaneous/plot_metadata_routing.html -
Time-related feature engineering — scikit-learn...
spring 0 1 0 False 6 False clear 9.84 14.395 0.81 0.0000 1 spring...spring 0 1 1 False 6 False clear 9.02 13.635 0.80 0.0000 2 spring...scikit-learn.org/stable/auto_examples/applications/plot_cyclical_feature_engineering.html -
ConstantKernel — scikit-learn 1.8.0 documentation
predict ( X [: 1 ,:], return_std = True ) (array([606.1]), array([0.248]))...ConstantKernel ( constant_value = 1.0 , constant_value_bounds = (1e-05,...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.ConstantKernel.html