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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/ja/_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/ja/_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_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_adaboost_regression.py
random_state=rng ) regr_1.fit(X, y) regr_2.fit(X, y) y_1 = regr_1.predict(X)...plt.plot(X, y_1, color=colors[1], label="n_estimators=1", linewidth=2)...scikit-learn.org/stable/_downloads/2da78c80da33b4e0d313b0a90b923ec8/plot_adaboost_regression.py -
plot_pca_iris.rst.txt
1].mean() + 1.5, X[y == label, 2].mean(),...np.choose(y, [1, 2, 0]).astype(float) ax.scatter(X[:, 0], X[:, 1], X[:,...scikit-learn.org/stable/_sources/auto_examples/decomposition/plot_pca_iris.rst.txt -
plot_adaboost_regression.ipynb
\nregr_1.fit(X, y)\nregr_2.fit(X, y)\n\ny_1 = regr_1.predict(X)\ny_2...samples\")\nplt.plot(X, y_1, color=colors[1], label=\"n_estimators=1\", linew...scikit-learn.org/stable/_downloads/38e826c9e3778d7de78b2fc671fd7903/plot_adaboost_regression.ipynb -
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_adaboost_regression.rst.txt
random_state=rng ) regr_1.fit(X, y) regr_2.fit(X, y) y_1 = regr_1.predict(X)...plt.plot(X, y_1, color=colors[1], label="n_estimators=1", linewidth=2)...scikit-learn.org/stable/_sources/auto_examples/ensemble/plot_adaboost_regression.rst.txt -
plot_pca_iris.py
1].mean() + 1.5, X[y == label, 2].mean(),...np.choose(y, [1, 2, 0]).astype(float) ax.scatter(X[:, 0], X[:, 1], X[:,...scikit-learn.org/stable/_downloads/1168f82083b3e70f31672e7c33738f8d/plot_pca_iris.py