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StratifiedShuffleSplit — scikit-learn 1.6.0 doc...
2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 ,...Test: index=[0 2 3] Fold 2: Train: index=[5 0 2] Test: index=[4...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedShuffleSplit.html -
PLSRegression — scikit-learn 1.7.dev0 documenta...
[ 2. , 2. , 2. ], [ 2. , 5. , 4. ]] >>> y =...= [[ 0.1 , - 0.2 ], [ 0.9 , 1.1 ], [ 6.2 , 5.9 ], [ 11.9 , 12.3...scikit-learn.org/dev/modules/generated/sklearn.cross_decomposition.PLSRegression.html -
plot_classifier_comparison.zip
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/ce35bcc69acbd491cf7ac77fa17889d5/plot_classifier_comparison.zip -
LinearRegression — scikit-learn 1.7.dev0 docume...
2 ], [ 2 , 2 ], [ 2 , 3 ]]) >>> # y = 1 * x_0 + 2 * x_1...float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...scikit-learn.org/dev/modules/generated/sklearn.linear_model.LinearRegression.html -
shuffle — scikit-learn 1.6.0 documentation
2)> >>> X_sparse . toarray () array([[0., 0.], [2., 1.],...y array([2, 1, 0]) >>> shuffle ( y , n_samples = 2 , random_state...scikit-learn.org/stable/modules/generated/sklearn.utils.shuffle.html -
mean_tweedie_deviance — scikit-learn 1.6.0 docu...
y_true = [ 2 , 0 , 1 , 4 ] >>> y_pred = [ 0.5 , 0.5 , 2. , 2. ] >>>...>= 0 and y_pred > 0. 1 < p < 2 : Compound Poisson distribution....scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_tweedie_deviance.html -
plot_release_highlights_1_5_0.ipynb
nothing;\n- each false negative costs 2;\n- each false positive costs...normalize=\"all\").ravel()\n return tp - 2 * fn - 0.1 * fp\n\n\nprint(\"Untuned...scikit-learn.org/stable/_downloads/ae2d0a2ad69c5df5b93e5ea5c87d56b2/plot_release_highlights_1_5_0... -
PowerTransformer — scikit-learn 1.7.dev0 docume...
2 ], [ 3 , 2 ], [ 4 , 5 ]] >>> print...X < 0 and lambda_ != 2 : X = 1 - ( - ( 2 - lambda_ ) * X_trans...scikit-learn.org/dev/modules/generated/sklearn.preprocessing.PowerTransformer.html -
SVC — scikit-learn 1.6.0 documentation
[ - 2 , - 1 ], [ 1 , 1 ], [ 2 , 1 ]]) >>> y = np...np . array ([ 1 , 1 , 2 , 2 ]) >>> from sklearn.svm import SVC...scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html -
Hotspots in Elasticsearch and how to resolve th...
f ( 2 − 2 ) + 0.55 f ( 0 − 0 ) = 0 weightNode1 = 0.45f(2 - 2)...f ( 2 − 2 ) + 0.55 f ( 0 − 0 ) = 0 w e i g h t N o d e 2 = 0.45...www.elastic.co/search-labs/blog/hotspot-elasticsearch-autoops