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HDBSCAN — scikit-learn 1.8.0 documentation
means 1 unless in a joblib.parallel_backend context. -1 means.... labels_ ) . tolist () [-1, 0, 1, 2, 3, 4, 5, 6, 7] dbscan_clustering...scikit-learn.org/stable/modules/generated/sklearn.cluster.HDBSCAN.html -
Spectral clustering for image segmentation R...
[ 0 ]) ** 2 + ( y - center1 [ 1 ]) ** 2 < radius1 ** 2 circle2...[ 0 ]) ** 2 + ( y - center2 [ 1 ]) ** 2 < radius2 ** 2 circle3...scikit-learn.org/stable/auto_examples/cluster/plot_segmentation_toy.html -
HistGradientBoostingRegressor — scikit-le...
scikit-learn 1.1 Release Highlights for scikit-learn 1.1 Release Highlights...version 1.1: Added option ‘quantile’. Changed in version 1.3: Added...scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingRegressor.html -
MLPRegressor — scikit-learn 1.8.0 documen...
returns f(x) = 1 / (1 + exp(-x)). ‘tanh’, the hyperbolic...random_state = 1 , max_iter = 2000 , tol = 0.1 ) >>>...scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPRegressor.html -
8.3. Generated datasets — scikit-learn 1....
1.1. Single label # make_blobs creates..."n_informative" : 1 , "n_clusters_per_class" : 1 , "n_classes"...scikit-learn.org/stable/datasets/sample_generators.html -
Visualizing the probabilistic predictions of a ...
uniform ( low =- 1 , high = 1 , size = ( n_samples , 2...xor [ "Feature #1" ] + noise [:, 1 ] > 0 ) X = xor...scikit-learn.org/stable/auto_examples/ensemble/plot_voting_decision_regions.html -
GradientBoostingClassifier — scikit-learn...
1 , n_estimators = 100 , subsample = 1.0 , criterion...in the range [1, inf) . subsample float, default=1.0 The fraction...scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingClassifier.html -
make_hastie_10_2 — scikit-learn 1.8.0 doc...
float64(-1.0), np.float64(1.0), np.float64(-1.0), np.float64(1.0),...i ] = 1 if np . sum ( X [ i ] ** 2 ) > 9.34 else - 1 Read more...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_hastie_10_2.html -
Hierarchical clustering with and without struct...
) t = 1.5 * np . pi * ( 1 + 3 * np . random . rand ( 1 , n_samples...n_samples , noise = noise ) X1 [:, 1 ] *= 0.5 # Make the roll thinner...scikit-learn.org/stable/auto_examples/cluster/plot_ward_structured_vs_unstructured.html -
Agglomerative clustering with different metrics...
1 , 1 ]) for l , color , n in zip...figure () plt . axes ([ 0 , 0 , 1 , 1 ]) for l , color in zip ( np...scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_clustering_metrics.html