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  1. Partial Dependence and Individual Conditional E...

    mask_training = X [ "year" ] == 0.0 X = X . drop ( columns = [ "year"...xtick_period = 6 , 12 fig , axs = plt . subplots ( nrows = 2 , figsize...
    scikit-learn.org/stable/auto_examples/inspection/plot_partial_dependence.html
    2025-07-18 16:23
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  2. Common pitfalls in the interpretation of coeffi...

    data = coefs , orient = "h" , palette = "dark:k" , alpha = 0.5...data = coefs , orient = "h" , color = "cyan" , saturation = 0.5...
    scikit-learn.org/stable/auto_examples/inspection/plot_linear_model_coefficient_interpretation.html
    2025-07-18 16:23
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  3. Gaussian Mixture Model Sine Curve — scikit-lear...

    any ( Y == i ): continue plt . scatter ( X [ Y == i , 0 ], X.... any ( Y == i ): continue plt . scatter ( X [ Y == i , 0 ], X...
    scikit-learn.org/stable/auto_examples/mixture/plot_gmm_sin.html
    2025-07-18 16:24
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  4. Gaussian Processes regression: basic introducto...

    linspace ( start = 0 , stop = 10 , num = 1_000 ) . reshape ( - 1 ,..., y , label = r "$f(x) = x \sin(x)$" , linestyle = "dotted" )...
    scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_noisy_targets.html
    2025-07-18 16:24
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  5. Metadata Routing — scikit-learn 1.7.1 documenta...

    n_features = 100 , 4 rng = np . random . RandomState ( 42 ) X = rng...( caller = "fit" , callee = "fit" ) . add ( caller = "predict"...
    scikit-learn.org/stable/auto_examples/miscellaneous/plot_metadata_routing.html
    2025-07-18 16:23
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  6. Release Highlights for scikit-learn 1.4 — sciki...

    noise = rng . normal ( loc = 0.0 , scale = 0.01 , size = n_samples...alpha = 0.5 , zorder =- 1 , label = "samples" , color = "tab:green"...
    scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_4_0.html
    2025-07-18 16:24
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  7. Probability Calibration curves — scikit-learn 1...

    range = ( 0 , 1 ), bins = 10 , label = name , color = colors...range = ( 0 , 1 ), bins = 10 , label = name , color = colors...
    scikit-learn.org/stable/auto_examples/calibration/plot_calibration_curve.html
    2025-07-18 16:24
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  8. Model Complexity Influence — scikit-learn 1.7.1...

    return_X_y = True ) train_size = 0.8 elif case == "classification"...data.""" if case == "regression" : X , y = datasets . load_diabetes...
    scikit-learn.org/stable/auto_examples/applications/plot_model_complexity_influence.html
    2025-07-18 16:24
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  9. Class Likelihood Ratios to measure classificati...

    axs = plt . subplots ( nrows = 3 , ncols = 2 , figsize = ( 15...response_method = "predict" , alpha = 0.5 , ax = ax , ) scatter = disp ....
    scikit-learn.org/stable/auto_examples/model_selection/plot_likelihood_ratios.html
    2025-07-18 16:23
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  10. Precision-Recall — scikit-learn 1.7.1 documenta...

    ) = plt . plot ( x [ y >= 0 ], y [ y >= 0 ], color = "gray"...name = "LinearSVC" , plot_chance_level = True , despine = True...
    scikit-learn.org/stable/auto_examples/model_selection/plot_precision_recall.html
    2025-07-18 16:23
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