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linear_model.rst.txt
array([[1, 0, 0, 0], [1, 0, 1, 0], [1, 1, 0, 0], [1, 1, 1, 1]]) >>>...1.e-05, 1.e-04, 1.e-03, 1.e-02, 1.e-01, 1.e+00, 1.e+01, 1.e+02, 1.e+03,...scikit-learn.org/stable/_sources/modules/linear_model.rst.txt -
model_evaluation.rst.txt
1, 1, 1, 1, 1] >>> y_pred = [0, 1, 0, 1, 0, 1, 0, 1] >>>...0, 0, 1, 1, 1, 1, 1] >>> y_pred = [0, 1, 0, 1, 0, 1, 0, 1] >>>...scikit-learn.org/stable/_sources/modules/model_evaluation.rst.txt -
about.rst.txt
btn-warning btn-big sk-donate-btn mb-1" href="https://numfocus.org/d...scikit-learn.org/stable/_sources/about.rst.txt -
plot_release_highlights_1_4_0.rst.txt
1, 6, np.nan]).reshape(-1, 1) y = [0, 0, 1, 1] forest...<td>1.0</td><td>0.0</td></tr><tr><td>-1.293993</td><td>1.0</...scikit-learn.org/stable/_sources/auto_examples/release_highlights/plot_release_highlights_1_4_0.r... -
index.rst.txt
the release of scikit-learn 1.1! Many bug fixes and improvements...glr_plot_release_highlights_1_1_0_thumb.png :alt: :ref:`sphx...scikit-learn.org/stable/_sources/auto_examples/index.rst.txt -
feature_extraction.rst.txt
array([[1, 1, 1, 0, 1, 1, 1, 0], [1, 1, 0, 1, 1, 1, 0, 1]]) In...array([[0, 1, 1, 1, 0, 0, 1, 0, 1], [0, 1, 0, 1, 0, 2, 1, 0, 1], [1,...scikit-learn.org/stable/_sources/modules/feature_extraction.rst.txt -
plot_classifier_comparison.rst.txt
C=1, random_state=42), GaussianProcessClass(1.0 * RBF(1.0),...max_features=1, random_state=42 ), MLPClassifier(alpha=1, max_iter=1000,...scikit-learn.org/stable/_sources/auto_examples/classification/plot_classifier_comparison.rst.txt -
user_guide.rst.txt
toctree:: :numbered: :maxdepth: 1 metadata_routing.rst...scikit-learn.org/stable/_sources/user_guide.rst.txt -
test.mm
1"> <node TEXT="Lorem ipsum. (ロ...raw.githubusercontent.com/codelibs/fess-testdata/master/xml/test.mm -
preprocessing.rst.txt
1. , 0.1], [4.4, 2.2, 1.1, 0.1], [4.4, 2.2, 1.2, 0.1], ...,...array([[1., 0., 0., 1., 0., 1.], [0., 1., 1., 0., 0., 1.]]) By...scikit-learn.org/stable/_sources/modules/preprocessing.rst.txt