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  1. Demo of affinity propagation clustering algorit...

    centers = [[ 1 , 1 ], [ - 1 , - 1 ], [ 1 , - 1 ]] X , labels_true...0 ]], [ cluster_center [ 1 ], x [ 1 ]], color = col [ "color"...
    scikit-learn.org/stable/auto_examples/cluster/plot_affinity_propagation.html
    Fri Dec 05 17:52:54 GMT 2025
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  2. 11. Common pitfalls and recommended practices &...

    n_features = 1 , noise = 1 ) >>> X_train ,...applies to using None . 11.3.1.1. Estimators # Passing instances...
    scikit-learn.org/stable/common_pitfalls.html
    Fri Dec 05 17:52:55 GMT 2025
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  3. Comparing Target Encoder with Other Encoders &#...

    scikit-learn 1.4 Release Highlights for scikit-learn 1.4 Gallery...Napa Cabernet Sauvignon Heitz 1 Spain Ripe aromas of fig, blackberry...
    scikit-learn.org/stable/auto_examples/preprocessing/plot_target_encoder.html
    Fri Dec 05 17:52:54 GMT 2025
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  4. Comparison of F-test and mutual information &#8...

    1 * N(0, 1), that is the third feature...sin ( 6 * np . pi * X [:, 1 ]) + 0.1 * np . random . randn ( 1000...
    scikit-learn.org/stable/auto_examples/feature_selection/plot_f_test_vs_mi.html
    Fri Dec 05 17:52:55 GMT 2025
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  5. Face completion with a multi-output estimators ...

    shape [ 1 ] # Upper half of the faces X_train...X_train = train [:, : ( n_pixels + 1 ) // 2 ] # Lower half of the faces...
    scikit-learn.org/stable/auto_examples/miscellaneous/plot_multioutput_face_completion.html
    Fri Dec 05 17:52:55 GMT 2025
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  6. Factor Analysis (with rotation) to visualize pa...

    vmin =- 1 , vmax = 1 ) ax . set_xticks ([ 0 , 1 , 2 , 3 ])...set_xticks ([ 0 , 1 ]) ax . set_xticklabels ([ "Comp. 1" , "Comp....
    scikit-learn.org/stable/auto_examples/decomposition/plot_varimax_fa.html
    Fri Dec 05 17:52:54 GMT 2025
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  7. Manifold Learning methods on a severed sphere &...

    67 sec modified: 1.3 sec ISO: 0.2 sec MDS: 0.79 sec...trans_data [ 0 ], trans_data [ 1 ], c = colors , cmap = plt . cm...
    scikit-learn.org/stable/auto_examples/manifold/plot_manifold_sphere.html
    Fri Dec 05 17:52:55 GMT 2025
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  8. SGD: Maximum margin separating hyperplane &#821...

    linspace ( - 1 , 5 , 10 ) yy = np . linspace ( - 1 , 5 , 10 ) X1...= p [ 0 ] levels = [ - 1.0 , 0.0 , 1.0 ] linestyles = [ "dashed"...
    scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_separating_hyperplane.html
    Fri Dec 05 17:52:54 GMT 2025
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  9. Scikit-learn governance and decision-making &#8...

    page: Requires +1 by a core contributor, no -1 by a core contributor...changes require +1 by two core contributors, no -1 by a core contributor...
    scikit-learn.org/stable/governance.html
    Fri Dec 05 17:52:54 GMT 2025
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  10. SVM: Separating hyperplane for unbalanced class...

    0 ]] clusters_std = [ 1.5 , 0.5 ] X , y = make_blobs (...kernel = "linear" , C = 1.0 ) clf . fit ( X , y ) # fit...
    scikit-learn.org/stable/auto_examples/svm/plot_separating_hyperplane_unbalanced.html
    Fri Dec 05 17:52:55 GMT 2025
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