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Getting Started — scikit-learn 1.8.0 docu...
dataset is easy array([1., 1., 1., 1., 1.]) Automatic parameter...transform ( X ) array([[-1., 1.], [ 1., -1.]]) Sometimes, you want...scikit-learn.org/stable/getting_started.html -
make_moons — scikit-learn 1.8.0 documenta...
) The integer labels (0 or 1) for class membership of each...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_moons.html -
make_column_transformer — scikit-learn 1....
means 1 unless in a joblib.parallel_backend context. -1 means...Added in version 1.5. Changed in version 1.7: The default value...scikit-learn.org/stable/modules/generated/sklearn.compose.make_column_transformer.html -
Version 0.22 — scikit-learn 1.8.0 documen...
given for both n_jobs=1 or n_jobs>1 both with shared memory...results between n_jobs=1 and n_jobs>1 due to the handling of...scikit-learn.org/stable/whats_new/v0.22.html -
Evaluation of outlier detection estimators R...
in pandas 1.5.1 were mapped to np.nan in pandas 2.0.1 X [ &quo...lue" , unknown_value =- 1 ) preprocessor = ColumnTransformer...scikit-learn.org/stable/auto_examples/miscellaneous/plot_outlier_detection_bench.html -
density — scikit-learn 1.8.0 documentation
between 0 and 1. Examples >>> from scipy...scikit-learn.org/stable/modules/generated/sklearn.utils.extmath.density.html -
Bunch — scikit-learn 1.8.0 documentation
>>> b = Bunch ( a = 1 , b = 2 ) >>> b [ 'b'...scikit-learn.org/stable/modules/generated/sklearn.utils.Bunch.html -
GaussianProcessClassifier — scikit-learn ...
1, 3.2, and 5.1 from [RW2006] . Internally,...None is passed, the kernel “1.0 * RBF(1.0)” is used as default. Note...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcessClassifier.html -
sklearn.preprocessing — scikit-learn 1.8....
Scale each feature to the [-1, 1] range without breaking the...data (set feature values to 0 or 1) according to a threshold. FunctionTransformer...scikit-learn.org/stable/api/sklearn.preprocessing.html -
Frequently Asked Questions — scikit-learn...
reshape ( - 1 , 1 ) >>> X array([[0], [1], [2]]) >>>...'brute' ) (array([0, 1]), array([ 0, 0, -1])) Note that the example...scikit-learn.org/stable/faq.html