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  1. Evaluation of outlier detection estimators — sc...

    ) s = ( y == 2 ) + ( y == 4 ) X = X . loc [ s ] y = y . loc [...random_state = 42 , return_X_y = True , as_frame = True ) y = ( y !=...
    scikit-learn.org/stable/auto_examples/miscellaneous/plot_outlier_detection_bench.html
    Fri May 31 14:06:04 UTC 2024
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  2. Illustration of prior and posterior Gaussian pr...

    nrows = 2 , sharex = True , sharey = True , figsize = ( 10 ,...nrows = 2 , sharex = True , sharey = True , figsize = ( 10 ,...
    scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_prior_posterior.html
    Fri May 31 14:06:06 UTC 2024
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  3. GMM covariances — scikit-learn 1.5.0 documentation

    bottom = 0.01 , top = 0.95 , hspace = 0.15 , wspace = 0.05 ,...scatterpoints = 1 , loc = "lower right" , prop = dict ( size = 12 ))...
    scikit-learn.org/stable/auto_examples/mixture/plot_gmm_covariances.html
    Fri May 31 14:06:06 UTC 2024
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  4. Classifier comparison — scikit-learn 1.5.0 docu...

    C = 0.025 , random_state = 42 ), SVC ( gamma = 2 , C = 1 ,...clf , X , cmap = cm , alpha = 0.8 , ax = ax , eps = 0.5 ) # Plot...
    scikit-learn.org/stable/auto_examples/classification/plot_classifier_comparison.html
    Fri May 31 14:06:06 UTC 2024
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  5. Probability Calibration for 3-class classificat...

    y = make_blobs ( n_samples = 2000 , n_features = 2 , centers...centers = 3 , random_state = 42 , cluster_std = 5.0 ) X_train ,...
    scikit-learn.org/stable/auto_examples/calibration/plot_calibration_multiclass.html
    Fri May 31 14:06:06 UTC 2024
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  6. BallTree — scikit-learn 1.5.0 documentation

    return_distance == False (d,i) if return_distance == True d ndarray...count if count_only == True ind if count_only == False and return_distance...
    scikit-learn.org/stable/modules/generated/sklearn.neighbors.BallTree.html
    Fri May 31 14:06:07 UTC 2024
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  7. Gradient Boosting Out-of-Bag estimates — scikit...

    n_splits = None ): cv = KFold ( n_splits = n_splits ) cv_clf = ensemble...) x1 = random_state . uniform ( size = n_samples ) x2 = random_state...
    scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_oob.html
    Fri May 31 14:06:06 UTC 2024
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  8. Understanding the decision tree structure — sci...

    iris = load_iris () X = iris . data y = iris . target...y_test = train_test_split ( X , y , random_state = 0 ) clf = DecisionTreeClassifi...
    scikit-learn.org/stable/auto_examples/tree/plot_unveil_tree_structure.html
    Fri May 31 14:06:06 UTC 2024
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  9. Multiclass Receiver Operating Characteristic (R...

    pair_list ): a_mask = y_test == label_a b_mask = y_test == label_b ab_mask...color = color , ax = ax , plot_chance_level = ( class_id == 2 ),...
    scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html
    Fri May 31 14:06:04 UTC 2024
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  10. Two-class AdaBoost — scikit-learn 1.5.0 documen...

    [ y == i ], bins = 10 , range = plot_range , facecolor = c ,...n_features = 2 , n_classes = 2 , random_state = 1 ) X2 , y2 = make_gaussian_quantiles...
    scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_twoclass.html
    Fri May 31 14:06:04 UTC 2024
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