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ClassifierChain — scikit-learn 1.6.1 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 -
Comparing Nearest Neighbors with and without Ne...
StandardScaler n_neighbors = 1 dataset = datasets . load_iris.... scatter ( X [:, 0 ], X [:, 1 ], c = y , cmap = cmap_bold ,...scikit-learn.org/stable/auto_examples/neighbors/plot_nca_classification.html -
MLPClassifier — scikit-learn 1.6.1 documentation
:]) array([1, 0, 1, 0, 1]) >>> clf . score ( X_test..., validation_fraction = 0.1 , beta_1 = 0.9 , beta_2 = 0.999 ,...scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPClassifier.html -
BaggingClassifier — scikit-learn 1.6.1 document...
max_samples = 1.0 , max_features = 1.0 , bootstrap = True...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingClassifier.html -
BernoulliRBM — scikit-learn 1.6.1 documentation
1 , 1 ], [ 1 , 0 , 1 ], [ 1 , 1 , 1 ]]) >>> model...= 256 , * , learning_rate = 0.1 , batch_size = 10 , n_iter = 10...scikit-learn.org/stable/modules/generated/sklearn.neural_network.BernoulliRBM.html -
LinearSVC — scikit-learn 1.6.1 documentation
intercept term: [x_1, ..., x_n, 1] , where 1 corresponds to the...version 1.3: The "auto" option is added in version 1.3 and will...scikit-learn.org/stable/modules/generated/sklearn.svm.LinearSVC.html -
StackingRegressor — scikit-learn 1.6.1 document...
in version 1.1: The ‘prefit’ option was added in 1.1 Note A larger...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.ensemble.StackingRegressor.html -
Perceptron — scikit-learn 1.6.1 documentation
l1_ratio <= 1 . l1_ratio=0 corresponds to L2 penalty, l1_ratio=1 to L1....means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.linear_model.Perceptron.html -
StratifiedKFold — scikit-learn 1.6.1 documentation
array ([[ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]])...>>> y = np . array ([ 0 , 0 , 1 , 1 ]) >>> skf = StratifiedKFold...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedKFold.html -
MiniBatchKMeans — scikit-learn 1.6.1 documentation
array ([[ 1 , 2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 4 , 2...0 , 1 ], [ 2 , 2 ], ... [ 3 , 2 ], [ 5 , 5 ], [ 1 , - 1 ]]) >>>...scikit-learn.org/stable/modules/generated/sklearn.cluster.MiniBatchKMeans.html