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Prediction Latency — scikit-learn 1.7.2 documen...
1 , verbose = False ): """Generate...configuration , duration_secs = 0.1 ): """benchmark throughput for...scikit-learn.org/stable/auto_examples/applications/plot_prediction_latency.html -
available_if — scikit-learn 1.7.2 documentation
>>> obj = HelloIfEven ( 1 ) >>> hasattr ( obj , "say_hello"...scikit-learn.org/stable/modules/generated/sklearn.utils.metaestimators.available_if.html -
Early stopping of Stochastic Gradient Descent —...
class_1 = "8" ): """Load MNIST, select...fetch_openml ( "mnist_784" , version = 1 , as_frame = False ) # take only...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_early_stopping.html -
Balance model complexity and cross-validated sc...
within 1 standard deviation of the best accuracy score. [1] Hastie,...test_scores , axis = 1 ) - np . std ( test_scores , axis = 1 ), np . mean...scikit-learn.org/stable/auto_examples/model_selection/plot_grid_search_refit_callable.html -
Joint feature selection with multi-task Lasso —...
ylim ([ - 1.1 , 1.1 ]) plt . show () Total running...(( 1.0 + rng . randn ( 1 )) * times + 3 * rng . randn ( 1 ))...scikit-learn.org/stable/auto_examples/linear_model/plot_multi_task_lasso_support.html -
Outlier detection on a real data set — scikit-l...
EllipticEnvelope ( support_fraction = 1.0 , contamination = 0.25 ), "Robust...= load_wine ()[ "data" ][:, [ 1 , 2 ]] # two clusters fig , ax...scikit-learn.org/stable/auto_examples/applications/plot_outlier_detection_wine.html -
fetch_lfw_people — scikit-learn 1.7.2 documenta...
Added in version 1.5. delay float, default=1.0 Number of seconds...False , n_retries = 3 , delay = 1.0 ) [source] # Load the Labeled...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_lfw_people.html -
maxabs_scale — scikit-learn 1.7.2 documentation
1 , 2 ], [ - 1 , 0 , 1 ]] >>> maxabs_scale...column independently array([[-1. , 1. , 1. ], [-0.5, 0. , 0.5]]) >>>...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.maxabs_scale.html -
robust_scale — scikit-learn 1.7.2 documentation
independently array([[-1., 1., 1.], [ 1., -1., -1.]]) >>> robust_scale...robust_scale >>> X = [[ - 2 , 1 , 2 ], [ - 1 , 0 , 1 ]] >>> robust_scale...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.robust_scale.html -
euclidean_distances — scikit-learn 1.7.2 docume...
1 ], [ 1 , 1 ]] >>> # distance between...(n_samples_Y,) or (n_samples_Y, 1) or (1, n_samples_Y), default=None...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.euclidean_distances.html