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plot_release_highlights_1_6_0.zip
""" ========== Release Highlights for scikit-learn 1.6 ==========...========== .. currentmodule:: sklearn We are pleased to announce the...scikit-learn.org/stable/_downloads/151e78f803ff9f3154dd7dbbaf45e0b0/plot_release_highlights_1_6_0... -
Feature importances with a forest of trees — sc...
n_repeated = 0 , n_classes = 2 , random_state = 0 , shuffle = False ,...n_repeats = 10 , random_state = 42 , n_jobs = 2 ) elapsed_time = time...scikit-learn.org/stable/auto_examples/ensemble/plot_forest_importances.html -
RFECV — scikit-learn 1.6.1 documentation
step = 1 , min_features_to_select = 1 , cv = None , scoring...scoring = None , verbose = 0 , n_jobs = None , importance_getter...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.RFECV.html -
Perceptron — scikit-learn 1.6.1 documentation
fit_intercept = True , max_iter = 1000 , tol = 0.001 , shuffle = True...verbose = 0 , eta0 = 1.0 , n_jobs = None , random_state = 0 , early_stopping...scikit-learn.org/stable/modules/generated/sklearn.linear_model.Perceptron.html -
RepeatedKFold — scikit-learn 1.6.1 documentation
n_splits = 5 , n_repeats = 10 , random_state = None ) [source]...RepeatedKFold ( n_splits = 2 , n_repeats = 2 , random_state = 2652124 ) >>>...scikit-learn.org/stable/modules/generated/sklearn.model_selection.RepeatedKFold.html -
Multi-class AdaBoosted Decision Trees — scikit-...
n_features = 10 , n_classes = 3 , random_state = 1 ) We split the...n_estimators = 300 adaboost_clf = AdaBoostClassifier ( estimator = weak_learner...scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_multiclass.html -
Neighborhood Components Analysis Illustration —...
y = make_classification ( n_samples = 9 , n_features = 2 ,...n_informative = 2 , n_redundant = 0 , n_classes = 3 , n_clusters_per_class...scikit-learn.org/stable/auto_examples/neighbors/plot_nca_illustration.html -
MLPClassifier — scikit-learn 1.6.1 documentation
learning_rate_init = 0.001 , power_t = 0.5 , max_iter = 200 , shuffle = True...random_state = None , tol = 0.0001 , verbose = False , warm_start = False...scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPClassifier.html -
RidgeClassifier — scikit-learn 1.6.1 documentation
max_iter = None , tol = 0.0001 , class_weight = None , solver = 'auto'...( alpha = 1.0 , * , fit_intercept = True , copy_X = True , max_iter...scikit-learn.org/stable/modules/generated/sklearn.linear_model.RidgeClassifier.html -
Tags — scikit-learn 1.6.1 documentation
None = None , classifier_tags: ClassifierTags | None = None ,...RegressorTags | None = None , array_api_support: bool = False , no_validation:...scikit-learn.org/stable/modules/generated/sklearn.utils.Tags.html