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  1. A demo of the Spectral Co-Clustering algorithm ...

    consensus score: 1.000 # Authors: The scikit-learn...permutation ( data . shape [ 1 ]) data = data [ row_idx ][:,...
    scikit-learn.org/stable/auto_examples/bicluster/plot_spectral_coclustering.html
    Wed Nov 19 04:33:04 GMT 2025
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  2. Tweedie regression on insurance claims — ...

    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 19 04:33:04 GMT 2025
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  3. Demo of OPTICS clustering algorithm — sci...

    subplot ( G [ 1 , 0 ]) ax3 = plt . subplot ( G [ 1 , 1 ]) ax4 = plt...labels_ == - 1 , 0 ], X [ clust . labels_ == - 1 , 1 ], "k+"...
    scikit-learn.org/stable/auto_examples/cluster/plot_optics.html
    Wed Nov 19 04:33:04 GMT 2025
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  4. SGD: convex loss functions — scikit-learn...

    >= - 1 ] = ( 1 - z [ z >= - 1 ]) ** 2 loss [ z >= 1.0 ]...([ xmin , 0 , 0 , xmax ], [ 1 , 1 , 0 , 0 ], color = "gold"...
    scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_loss_functions.html
    Wed Nov 19 04:33:04 GMT 2025
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  5. Visualizing the stock market structure — ...

    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 19 04:33:03 GMT 2025
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  6. 8. Dataset loading utilities — scikit-lea...

    1. Toy datasets 8.1.1. Iris plants dataset 8.1.2. Diabetes...digits dataset 8.1.4. Linnerrud dataset 8.1.5. Wine recognition dataset...
    scikit-learn.org/stable/datasets.html
    Wed Nov 19 04:33:03 GMT 2025
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  7. Demonstrating the different strategies of KBins...

    strategies ) + 1 , i ) ax . scatter ( X [:, 0 ], X [:, 1 ], edgecolors.... linspace ( X [:, 1 ] . min (), X [:, 1 ] . max (), 300 ), )...
    scikit-learn.org/stable/auto_examples/preprocessing/plot_discretization_strategies.html
    Wed Nov 19 04:33:04 GMT 2025
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  8. Displaying estimators and complex pipelines &#8...

    C  1.0 fit_intercept  True intercept_scaling  1 class_weight ...C  1.0 fit_intercept  True intercept_scaling  1 class_weight ...
    scikit-learn.org/stable/auto_examples/miscellaneous/plot_estimator_representation.html
    Wed Nov 19 04:33:04 GMT 2025
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  9. Agglomerative clustering with and without struc...

    ) t = 1.5 * np . pi * ( 1 + 3 * np . random . rand ( 1 , n_samples..."single" )): plt . subplot ( 1 , 4 , index + 1 ) model = AgglomerativeCluster...
    scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_clustering.html
    Wed Nov 19 04:33:04 GMT 2025
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  10. 9. Computing with scikit-learn — scikit-l...

    1.1. Scaling with instances using out-of-core...Computing with scikit-learn # 9.1. Strategies to scale computationally:...
    scikit-learn.org/stable/computing.html
    Wed Nov 19 04:33:04 GMT 2025
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