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decomposition.rst.txt
array([[1, 1], [2, 1], [3, 1.2], [4, 1], [5, 0.8], [6, 1]]) >>>...np.array([[1, 0], [1, 6.1], [1, 0], [1, 4], [3.2, 1], [0, 4]])...scikit-learn.org/stable/_sources/modules/decomposition.rst.txt -
glossary.rst.txt
``[{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}]`` instead...instead of ``[{1:1}, {2:5}, {3:1}, {4:1}]``. The ``class_weight``...scikit-learn.org/stable/_sources/glossary.rst.txt -
grid_search.rst.txt
{'C': [1, 10, 100, 1000], 'kernel': ['linear']}, {'C': [1, 10,...``loguniform(1, 100)`` can be used instead of ``[1, 10, 100]``....scikit-learn.org/stable/_sources/modules/grid_search.rst.txt -
faq.rst.txt
reshape(-1, 1) >>> X array([[0], [1], [2]]) >>> # We...doctest: +SKIP (array([0, 1]), array([ 0, 0, -1])) Note that the example...scikit-learn.org/stable/_sources/faq.rst.txt -
testimonials.rst.txt
v-box"> Scikit-learn is our #1 toolkit for all things machine...used for originating at least 1 billion GBP worth of Zopa loans....scikit-learn.org/stable/_sources/testimonials/testimonials.rst.txt -
roadmap.rst.txt
cross-version safety from version 1.0. Note: Gael and Olivier think...scikit-learn.org/stable/_sources/roadmap.rst.txt -
ensemble.rst.txt
1, 2, np.nan]).reshape(-1, 1) >>> y = [0, 0, 1, 1] >>> gbdt...np.nan, 1, 2, np.nan]).reshape(-1, 1) >>> y = [0, 1, 0, 0, 1] >>>...scikit-learn.org/stable/_sources/modules/ensemble.rst.txt -
neighbors.rst.txt
array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])...np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])...scikit-learn.org/stable/_sources/modules/neighbors.rst.txt -
plot_kmeans_digits.rst.txt
1].min() - 1, reduced_data[:, 1].max() + 1 xx, yy =...reduced_data[:, 0].min() - 1, reduced_data[:, 0].max() + 1 y_min, y_max =...scikit-learn.org/stable/_sources/auto_examples/cluster/plot_kmeans_digits.rst.txt -
v1.3.rst.txt
_changes_1_3_1: Version 1.3.1 ========== **September..... _release_notes_1_3: ========== Version 1.3 ========== For a...scikit-learn.org/stable/_sources/whats_new/v1.3.rst.txt