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Visualizing cross-validation behavior in scikit...
scikit-learn 1.4 Release Highlights for scikit-learn 1.4 Gallery...10 ) percentiles_classes = [ 0.1 , 0.3 , 0.6 ] y = np . hstack...scikit-learn.org/stable/auto_examples/model_selection/plot_cv_indices.html -
check_random_state — scikit-learn 1.5.2 documen...
Gallery examples: Empirical evaluation of the impact of k-means initialization MNIST classification using multinomial logistic + L1 Manifold Learning methods on a severed sphere Face completion wit...scikit-learn.org/stable/modules/generated/sklearn.utils.check_random_state.html -
sklearn.feature_selection — scikit-learn 1.5.2 ...
Feature selection algorithms. These include univariate filter selection methods and the recursive feature elimination algorithm. User guide. See the Feature selection section for further details.scikit-learn.org/stable/api/sklearn.feature_selection.html -
sklearn.neural_network — scikit-learn 1.5.2 doc...
Models based on neural networks. User guide. See the Neural network models (supervised) and Neural network models (unsupervised) sections for further details.scikit-learn.org/stable/api/sklearn.neural_network.html -
sklearn.model_selection — scikit-learn 1.5.2 do...
Tools for model selection, such as cross validation and hyper-parameter tuning. User guide. See the Cross-validation: evaluating estimator performance, Tuning the hyper-parameters of an estimator, ...scikit-learn.org/stable/api/sklearn.model_selection.html -
get_data_home — scikit-learn 1.5.2 documentation
Gallery examples: Out-of-core classification of text documentsscikit-learn.org/stable/modules/generated/sklearn.datasets.get_data_home.html -
load_sample_images — scikit-learn 1.5.2 documen...
Skip to main content Back to top Ctrl + K GitHub load_sample_images # sklearn.datasets. load_sample_images ( ) [sourc...scikit-learn.org/stable/modules/generated/sklearn.datasets.load_sample_images.html -
make_s_curve — scikit-learn 1.5.2 documentation
Gallery examples: Comparison of Manifold Learning methods t-SNE: The effect of various perplexity values on the shapescikit-learn.org/stable/modules/generated/sklearn.datasets.make_s_curve.html -
enable_iterative_imputer — scikit-learn 1.5.2 d...
Enables IterativeImputer The API and results of this estimator might change without any deprecation cycle. Importing this file dynamically sets IterativeImputer as an attribute of the impute module:scikit-learn.org/stable/modules/generated/sklearn.experimental.enable_iterative_imputer.html -
Comparing random forests and the multi-output m...
RandomState ( 1 ) X = np . sort ( 200 * rng . rand ( 600 , 1 ) - 100...( y_test [:, 0 ], y_test [:, 1 ], edgecolor = "k" , c = "navy"...scikit-learn.org/stable/auto_examples/ensemble/plot_random_forest_regression_multioutput.html