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simplebar.min.css
s:none;z-index:-1}.simplebar-track{z-index:1;position:absolu...1px;overflow:hidden;z-index:-1;padding:0;margin:0;pointer-ev...fess.codelibs.org/_static/assets/vendor/simplebar/dist/simplebar.min.css -
prism-toolbar.css
toolbar { opacity: 1; } /* Separate line b/c rules...within > .toolbar { opacity: 1; } div.code-toolbar > .toolbar...fess.codelibs.org/_static/assets/vendor/prismjs/plugins/toolbar/prism-toolbar.css -
prism.css
word-wrap: normal; line-height: 1.5; -moz-tab-size: 4; -o-tab-size:...fess.codelibs.org/ja/_static/assets/vendor/prismjs/themes/prism.css -
plot_release_highlights_1_5_0.py
array( [ [-1.1, 1.1, 1.1], [3.9, -1.2, np.nan], [np.nan, 1.3, np.nan],...np.nan], [-0.1, -1.4, -1.4], [-4.9, 1.5, -1.5], [np.nan, 1.6, 1.6], ]...scikit-learn.org/stable/_downloads/ba0cfc16d7953e1c2c6912b6beca1e91/plot_release_highlights_1_5_0.py -
plot_pca_iris.ipynb
1].mean() + 1.5,\n X[y == label, 2].mean(),\n...np.choose(y, [1, 2, 0]).astype(float)\nax.scatter(X[:, 0], X[:, 1], X[:,...scikit-learn.org/stable/_downloads/46b6a23d83637bf0f381ce9d8c528aa2/plot_pca_iris.ipynb -
plot_discretization_strategies.py
8]]) centers_1 = np.array([[0, 0], [3, 1]]) # construct the...len(strategies) + 1, i) ax.scatter(X[:, 0], X[:, 1], edgecolors="k")...scikit-learn.org/stable/_downloads/43e84df0b93ff974da370e8da900f2ee/plot_discretization_strategie... -
plot_kmeans_digits.ipynb
1].min() - 1, reduced_data[:, 1].max() + 1\nxx, yy =...reduced_data[:, 0].min() - 1, reduced_data[:, 0].max() + 1\ny_min, y_max =...scikit-learn.org/stable/_downloads/6bf322ce1724c13e6e0f8f719ebd253c/plot_kmeans_digits.ipynb -
plot_classifier_comparison.ipynb
C=1, random_state=42),\n GaussianProcessClass(1.0 * RBF(1.0),...max_features=1, random_state=42\n ),\n MLPClassifier(alpha=1, max_iter=1000,...scikit-learn.org/stable/_downloads/3438aba177365cb595921cf18806dfa7/plot_classifier_comparison.ipynb -
plot_discretization_strategies.ipynb
8]])\ncenters_1 = np.array([[0, 0], [3, 1]])\n\n# construct...len(strategies) + 1, i)\n ax.scatter(X[:, 0], X[:, 1], edgecolors=\"k\")\n...scikit-learn.org/stable/_downloads/adc9be3b7acc279025dad9ee4ce92038/plot_discretization_strategie... -
plot_kmeans_digits.py
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/_downloads/5a87b25ba023ee709595b8d02049f021/plot_kmeans_digits.py