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  1. Poisson regression and non-normal loss — scikit...

    axes = plt . subplots ( nrows = 2 , ncols = 4 , figsize = ( 16..., ax = plt . subplots ( nrows = 2 , ncols = 2 , figsize = ( 12...
    scikit-learn.org/stable/auto_examples/linear_model/plot_poisson_regression_non_normal_loss.html
    Thu Apr 10 21:02:03 UTC 2025
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  2. Decision Boundaries of Multinomial and One-vs-R...

    n_samples = 1_000 , centers = centers , random_state = 40 ) transformation..., ax = plt . subplots ( figsize = ( 6 , 4 )) scatter = ax . scatter...
    scikit-learn.org/stable/auto_examples/linear_model/plot_logistic_multinomial.html
    Thu Apr 10 21:02:03 UTC 2025
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  3. favicon_64x64_16bit.png

    35273367 width=64, height=64, bitDepth=8, colorType=RGBAlpha, c...whitePointX=31270, whitePointY=32900, redX=64000, redY=33000, greenX=30000,...
    www.elastic.co/favicon_64x64_16bit.png
    Mon Mar 24 20:10:51 UTC 2025
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  4. Multilabel classification — scikit-learn 1.6.1 ...

    if transform == "pca" : X = PCA ( n_components = 2 ) . fit_transform...elif transform == "cca" : X = CCA ( n_components = 2 ) . fit ( X...
    scikit-learn.org/stable/auto_examples/miscellaneous/plot_multilabel.html
    Thu Apr 10 21:02:03 UTC 2025
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  5. plot_multi_metric_evaluation.rst.txt

    py: ========== Demonstration of multi-metric...cross_val_score and GridSearchCV ========== Multiple metric parameter...
    scikit-learn.org/stable/_sources/auto_examples/model_selection/plot_multi_metric_evaluation.rst.txt
    Wed Apr 09 14:12:58 UTC 2025
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  6. Plot multi-class SGD on the iris dataset — scik...

    mean ( axis = 0 ) std = X . std ( axis = 0 ) X = ( X - mean ) /...dataset X = iris . data [:, : 2 ] y = iris . target colors = "bry"...
    scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_iris.html
    Thu Apr 10 21:02:03 UTC 2025
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  7. Plot class probabilities calculated by the Voti...

    random_state = 123 ) clf2 = RandomForestClassifi ( n_estimators = 100..., random_state = 123 ) clf3 = GaussianNB () X = np . array ([[...
    scikit-learn.org/stable/auto_examples/ensemble/plot_voting_probas.html
    Thu Apr 10 21:02:03 UTC 2025
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  8. Effect of model regularization on training and ...

    n_informative = 50 , shuffle = False , noise = 1.0 , coef = True , random_state...color = "k" , linewidth = 2 , linestyle = "--" , label = f "Optimum...
    scikit-learn.org/stable/auto_examples/model_selection/plot_train_error_vs_test_error.html
    Thu Apr 10 21:02:03 UTC 2025
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  9. RadiusNeighborsTransformer — scikit-learn 1.6.1...

    leaf_size = 30 , metric = 'minkowski' , p = 2 , metric_params = None...* , mode = 'distance' , radius = 1.0 , algorithm = 'auto' , leaf_size...
    scikit-learn.org/stable/modules/generated/sklearn.neighbors.RadiusNeighborsTransformer.html
    Thu Apr 10 21:02:05 UTC 2025
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  10. non_negative_factorization — scikit-learn 1.6.1...

    W = None , H = None , n_components = 'auto' , * , init = None...tol = 0.0001 , max_iter = 200 , alpha_W = 0.0 , alpha_H = 'same'...
    scikit-learn.org/stable/modules/generated/sklearn.decomposition.non_negative_factorization.html
    Thu Apr 10 21:02:05 UTC 2025
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