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  1. compute_optics_graph — scikit-learn 1.7.2 docum...

    1. , 1. , 4.12]) >>> reachability array([ inf, 3.16, 1.41,...1.41, 4.12, 1. , 5. ]) >>> predecessor array([-1, 0, 1, 5, 3, 2])...
    scikit-learn.org/stable/modules/generated/sklearn.cluster.compute_optics_graph.html
    Wed Nov 12 21:05:28 UTC 2025
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  2. Prediction Intervals for Gradient Boosting Regr...

    common_params ) all_models [ "q %1.2f " % alpha ] = gbr . fit ( X_train...0.5 , 0.95 ]: metrics [ "pbl= %1.2f " % alpha ] = mean_pinball_loss...
    scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_quantile.html
    Wed Nov 12 21:05:27 UTC 2025
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  3. cluster_optics_xi — scikit-learn 1.7.2 document...

    1, 1, 1]) >>> clusters array([[0, 2],...min_samples int > 1 or float between 0 and 1 The same as the min_samples...
    scikit-learn.org/stable/modules/generated/sklearn.cluster.cluster_optics_xi.html
    Wed Nov 12 21:05:28 UTC 2025
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  4. d2_tweedie_score — scikit-learn 1.7.2 documenta...

    1 , 2.5 , 7 ] >>> y_pred = [ 1 , 1 , 5 , 3.5 ] >>>...explained. Best possible score is 1.0 and it can be negative (because...
    scikit-learn.org/stable/modules/generated/sklearn.metrics.d2_tweedie_score.html
    Wed Nov 12 21:05:27 UTC 2025
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  5. Demo of OPTICS clustering algorithm — scikit-le...

    subplot ( G [ 1 , 0 ]) ax3 = plt . subplot ( G [ 1 , 1 ]) ax4 = plt...labels_ == - 1 , 0 ], X [ clust . labels_ == - 1 , 1 ], "k+" , alpha...
    scikit-learn.org/stable/auto_examples/cluster/plot_optics.html
    Wed Nov 12 21:05:27 UTC 2025
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  6. Tweedie regression on insurance claims — scikit...

    tweedie_powers = [ 1.5 , 1.7 , 1.8 , 1.9 , 1.99 , 1.999 , 1.9999 ] scores_product_model...dev p=1.9990 1.914574e+03 1.914370e+03 1.914537e+03 1.914388e+03...
    scikit-learn.org/stable/auto_examples/linear_model/plot_tweedie_regression_insurance_claims.html
    Wed Nov 12 21:05:28 UTC 2025
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  7. 2. Unsupervised learning — scikit-learn 1.7.2 d...

    1. Gaussian mixture models 2.1.1. Gaussian Mixture 2.1.2....Mixture 2.2. Manifold learning 2.2.1. Introduction 2.2.2. Isomap 2.2.3....
    scikit-learn.org/stable/unsupervised_learning.html
    Tue Nov 11 16:53:27 UTC 2025
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  8. compute_class_weight — scikit-learn 1.7.2 docum...

    compute_class_weight >>> y = [ 1 , 1 , 1 , 1 , 0 , 0 ] >>> compute_class_weight...unique ( y ), y = y ) array([1.5 , 0.75]) On this page This Page...
    scikit-learn.org/stable/modules/generated/sklearn.utils.class_weight.compute_class_weight.html
    Wed Nov 12 21:05:28 UTC 2025
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  9. Visualizing the stock market structure — scikit...

    index ] = 1 dy = y - embedding [ 1 ] dy [ index ] = 1 this_dx =...alphas = np . logspace ( - 1.5 , 1 , num = 10 ) edge_model = covariance...
    scikit-learn.org/stable/auto_examples/applications/plot_stock_market.html
    Wed Nov 12 21:05:27 UTC 2025
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  10. Plot classification boundaries with different S...

    1 , 1 , 1 , 1 , 1 , 1 , 1 , 1 ]) # Plotting settings...], [ - 1.5 , - 1.0 ], [ - 1.4 , - 0.9 ], [ - 1.3 , - 1.2 ], [...
    scikit-learn.org/stable/auto_examples/svm/plot_svm_kernels.html
    Wed Nov 12 21:05:27 UTC 2025
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