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Quickstart: Time series data stream basics | El...
"total": 2, "successful": 2, "failed":..."total": 2, "successful": 2, "failed":...www.elastic.co/docs/manage-data/data-store/data-streams/quickstart-tsds -
Comparing different hierarchical linkage method...
xlim ( - 2.5 , 2.5 ) plt . ylim ( - 2.5 , 2.5 ) plt . xticks...t; : 2 }), ( noisy_moons , { "n_clusters" : 2 }), (...scikit-learn.org/stable/auto_examples/cluster/plot_linkage_comparison.html -
8.3. Generated datasets — scikit-learn 1....
"n_classes" : 2 }, { "n_informative" : 2 , "n_c..._class" : 2 , "n_classes" : 2 }, { "n_informative"...scikit-learn.org/stable/datasets/sample_generators.html -
Version 0.15 — scikit-learn 1.8.0 documen...
Marsi 2 csytracy 2 LK 2 Vlad Niculae 2 Laurent Direr 2 Erik Shilts...Liau 2 abhishek thakur 2 James Yu 2 Rohit Sivaprasad 2 Roland...scikit-learn.org/stable/whats_new/v0.15.html -
explained_variance_score — scikit-learn 1...
= [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2...= [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2...scikit-learn.org/stable/modules/generated/sklearn.metrics.explained_variance_score.html -
make_friedman1 — scikit-learn 1.8.0 docum...
2 ] - 0.5 ) ** 2 + 10 * X [:, 3 ] + 5 *...in Friedman [1] and Breiman [2]. Inputs X are independent features...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_friedman1.html -
mean_gamma_deviance — scikit-learn 1.8.0 ...
2. , 2. ] >>> mean_gamma_deviance...with the power parameter power=2 . It is invariant to scaling of...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_gamma_deviance.html -
GMM covariances — scikit-learn 1.8.0 docu...
covariances_ [ n ][: 2 , : 2 ] elif gmm . covariance_type...covariances = gmm . covariances_ [: 2 , : 2 ] elif gmm . covariance_type...scikit-learn.org/stable/auto_examples/mixture/plot_gmm_covariances.html -
FastICA on 2D point clouds — scikit-learn...
subplot ( 2 , 2 , 2 ) plot_samples ( X / np ....1.5 , size = ( 20000 , 2 )) S [:, 0 ] *= 2.0 # Mix data A = np ....scikit-learn.org/stable/auto_examples/decomposition/plot_ica_vs_pca.html -
plot_classifier_comparison.py
make_classification( n_features=2, n_redundant=0, n_informative=2, random_state=1,...rng = np.random.RandomState(2) X += 2 * rng.uniform(size=X.shape)...scikit-learn.org/stable/_downloads/2da0534ab0e0c8241033bcc2d912e419/plot_classifier_comparison.py