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VotingClassifier — scikit-learn 1.8.0 documenta...
([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2...2 , 1 ], [ 3 , 2 ]]) >>> y = np . array ([ 1 , 1 , 1 , 2 , 2...scikit-learn.org/stable/modules/generated/sklearn.ensemble.VotingClassifier.html -
compute_optics_graph — scikit-learn 1.8.0 docum...
1. , 1. , 4.12]) >>> reachability array([ inf, 3.16, 1.41,...1.41, 4.12, 1. , 5. ]) >>> predecessor array([-1, 0, 1, 5, 3, 2])...scikit-learn.org/stable/modules/generated/sklearn.cluster.compute_optics_graph.html -
ClassifierChain — scikit-learn 1.8.0 documentation
X_test ) array([[1., 1., 0.], [1., 0., 0.], [0., 1., 0.]]) >>> chain...order = [ 0 , 1 , 2 , ... , Y . shape [ 1 ] - 1 ] The order of...scikit-learn.org/stable/modules/generated/sklearn.multioutput.ClassifierChain.html -
SelectFpr — scikit-learn 1.8.0 documentation
Added in version 1.0. See also f_classif ANOVA F-value..."x1", ..., "x(n_features_in_ - 1)"] . If input_features is an array-like,...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.SelectFpr.html -
SparseCoder — scikit-learn 1.8.0 documentation
1 , 0 ], ... [ - 1 , - 1 , 2 ], ... [ 1 , 1 , 1 ], ......>>> X = np . array ([[ - 1 , - 1 , - 1 ], [ 0 , 0 , 3 ]]) >>> dictionary...scikit-learn.org/stable/modules/generated/sklearn.decomposition.SparseCoder.html -
LabelEncoder — scikit-learn 1.8.0 documentation
classes_ array([1, 2, 6]) >>> le . transform ([ 1 , 1 , 2 , 6 ]) array([0,...array([0, 0, 1, 2]...) >>> le . inverse_transform ([ 0 , 0 , 1 , 2 ])...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html -
MultiTaskLasso — scikit-learn 1.8.0 documentation
1 ) >>> clf . fit ([[ 0 , 1 ], [ 1 , 2 ], [ 2 ,...0 ], [ 1 , 1 ], [ 2 , 3 ]]) MultiTaskLasso(alpha=0.1) >>> print...scikit-learn.org/stable/modules/generated/sklearn.linear_model.MultiTaskLasso.html -
KernelRidge — scikit-learn 1.8.0 documentation
alpha = 1.0 ) >>> krr . fit ( X , y ) KernelRidge(alpha=1.0) fit...sklearn.kernel_ridge. KernelRidge ( alpha = 1 , * , kernel = 'linear' , gamma...scikit-learn.org/stable/modules/generated/sklearn.kernel_ridge.KernelRidge.html -
GridSearchCV — scikit-learn 1.8.0 documentation
means 1 unless in a joblib.parallel_backend context. -1 means...0.70 … 4 ‘rbf’ 0.1 – 0.80 … 3 ‘rbf’ 0.2 – 0.93 … 1 will be represented...scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html -
TunedThresholdClassifierCV — scikit-learn 1.8.0...
means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn 1.5 Release Highlights for scikit-learn 1.5 On this...scikit-learn.org/stable/modules/generated/sklearn.model_selection.TunedThresholdClassifierCV.html