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  1. Categorical Feature Support in Gradient Boostin...

    "Functional" , "MasVnrType" , "HouseStyle" , "FireplaceQu" , "ExterCond"...[ "3SsnPorch" , "Fireplaces" , "BsmtHalfBath" , "HalfBath" , "GarageCars"...
    scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_categorical.html
    Sat Aug 02 00:15:37 UTC 2025
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  2. Gaussian processes on discrete data structures ...

    **- 0.5 ))) plt . xticks ( np . arange ( len ( X )), X ) plt...( np . diag ( D **- 0.5 ) . dot ( K ) . dot ( np . diag ( D **-...
    scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_on_structured_data.html
    Sat Aug 02 00:15:37 UTC 2025
      120.9K bytes
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  3. Curve Fitting with Bayesian Ridge Regression ...

    set_ylim ( - 1.3 , 1.3 ) ax . legend () title = "$ \\ alpha$_init$=...size ) x_test = np . linspace ( 0.0 , 1.0 , 100 ) Fit by cubic polynomial...
    scikit-learn.org/stable/auto_examples/linear_model/plot_bayesian_ridge_curvefit.html
    Sat Aug 02 00:15:35 UTC 2025
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  4. Generalized Linear Models scikit-learn 1.7.1 ...

    Lasso, Lasso-LARS, and Elastic Net paths Lasso, Lasso-LARS, and...selection: AIC-BIC / cross-validation Lasso model selection: AIC-BIC /...
    scikit-learn.org/stable/auto_examples/linear_model/index.html
    Sat Aug 02 00:15:35 UTC 2025
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  5. Faces dataset decompositions scikit-learn 1.7...

    ( 2.0 * n_col , 2.3 * n_row ), facecolor = "white" , constrained_layout...h_pad = 0.02 , hspace = 0 , wspace = 0 ) fig . set_edgecolor ( "black"...
    scikit-learn.org/stable/auto_examples/decomposition/plot_faces_decomposition.html
    Sat Aug 02 00:15:37 UTC 2025
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  6. Gradient Boosting regression scikit-learn 1.7...

    plt . subplot ( 1 , 1 , 1 ) plt . title ( "Deviance" ) plt . plot..."min_samples_split" : 5 , "learning_rate" : 0.01 , "loss" : "squared_error"...
    scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_regression.html
    Sat Aug 02 00:15:37 UTC 2025
      110K bytes
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  7. Probabilistic predictions with Gaussian process...

    Likelihood (optimized): -3.875 Accuracy: 1.000 (initial) 1.000 (optimized)..."Log-loss: %.3f (initial) %.3f (optimized)" % ( log_loss ( y [:...
    scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc.html
    Sat Aug 02 00:15:37 UTC 2025
      110.7K bytes
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  8. Ledoit-Wolf vs OAS estimation scikit-learn 1....

    oa_mse . mean ( 1 ), yerr = oa_mse . std ( 1 ), label = "OAS" , color...( 1 ), label = "Ledoit-Wolf" , color = "navy" , lw = 2 , ) plt...
    scikit-learn.org/stable/auto_examples/covariance/plot_lw_vs_oas.html
    Sat Aug 02 00:15:37 UTC 2025
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  9. Plot randomly generated multilabel dataset sc...

    Class P(C) P(w0|C) P(w1|C) red 0.32 0.55 0.45 blue 0.26 0.79 0.21...= np . array ( [ "!" , "#FF3333" , # red "#0198E1" , # blue "#BF5FFF"...
    scikit-learn.org/stable/auto_examples/datasets/plot_random_multilabel_dataset.html
    Sat Aug 02 00:15:37 UTC 2025
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  10. Ensemble methods scikit-learn 1.7.1 documenta...

    Boosting Out-of-Bag estimates Gradient Boosting Out-of-Bag estimates...bagging: bias-variance decomposition Two-class AdaBoost Two-class AdaBoost...
    scikit-learn.org/stable/auto_examples/ensemble/index.html
    Sat Aug 02 00:15:35 UTC 2025
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