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plot_pca_iris.ipynb
text3D(\n X[y == label, 0].mean(),\n X[y == label, 1].mean()...,\n bbox=dict(alpha=0.5, edgecolor=\"w\", facecolor=\"w\"),\n...scikit-learn.org/stable/_downloads/46b6a23d83637bf0f381ce9d8c528aa2/plot_pca_iris.ipynb -
sg_gallery.css
:root[data-theme="auto"], html[data-theme="auto"], body[data-theme="auto"]...:root, html[data-theme="light"], body[data-theme="light"]{ --sg-tooltip-foreground:...scikit-learn.org/dev/_static/sg_gallery.css -
873de304b9bd7a1b.css
:rotate(45deg)}[aria-expanded=true] .AccordionFAQ_accordion_...__X8xTr:before,[aria-selected=true] .AccordionFAQ_accordion_...www.elastic.co/_next/static/css/873de304b9bd7a1b.css -
plot_release_highlights_1_4_0.py
""" ========== Release Highlights for scikit-learn 1.4 ==========...noise = rng.normal(loc=0.0, scale=0.01, size=n_samples) y = 5 *...scikit-learn.org/stable/_downloads/c15cce0dbcd8722cb5638987eff985c0/plot_release_highlights_1_4_0.py -
plot_adaboost_regression.py
""" ========== Decision Tree Regression with AdaBoost ==========...y_1, color=colors[1], label="n_estimators=1", linewidth=2) plt.plot(X,...scikit-learn.org/stable/_downloads/2da78c80da33b4e0d313b0a90b923ec8/plot_adaboost_regression.py -
plot_discretization_strategies.ipynb
cluster_std=0.5,\n centers=centers_0,\n random_state=random_state,\n...)[0],\n]\n\nfigure = plt.figure(figsize=(14, 9))\ni = 1\nfor ds_cnt,...scikit-learn.org/stable/_downloads/adc9be3b7acc279025dad9ee4ce92038/plot_discretization_strategie... -
plot_adaboost_regression.ipynb
color=colors[1], label=\"n_estimators=1\", linewidth=2)\nplt.plot(X,...color=colors[2], label=\"n_estimators=300\", linewidth=2)\np...scikit-learn.org/stable/_downloads/38e826c9e3778d7de78b2fc671fd7903/plot_adaboost_regression.ipynb -
plot_kmeans_digits.py
metrics): ========== ========== Shorthand full name ========== ==========...silhouette coefficient ========== ========== """ # %% # Load the...scikit-learn.org/stable/_downloads/5a87b25ba023ee709595b8d02049f021/plot_kmeans_digits.py -
plot_classifier_comparison.ipynb
C=0.025, random_state=42),\n SVC(gamma=2, C=1, random_state=42),\n...max_depth=5, n_estimators=10, max_features=1, random_state=42\n ),\n...scikit-learn.org/stable/_downloads/3438aba177365cb595921cf18806dfa7/plot_classifier_comparison.ipynb -
sg_gallery-dataframe.css
#L587-L619 */ html[data-theme="light"] { --sg-text-color: #000;...165, 245, 0.2); } html[data-theme="dark"] { --sg-text-color: #fff;...scikit-learn.org/stable/_static/sg_gallery-dataframe.css