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Results 111 - 120 of 813 for tests (0.13 sec)

  1. Gradient Boosting regularization — scikit-learn...

    X_test , y_train , y_test = train_test_split ( X ,...( X_test )): test_deviance [ i ] = 2 * log_loss ( y_test , y_proba...
    scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_regularization.html
    Sat Aug 23 16:32:03 UTC 2025
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  2. Precision-Recall — scikit-learn 1.7.1 documenta...

    and test X_train , X_test , y_train , y_test = train_test_split...and test X_train , X_test , Y_train , Y_test = train_test_split...
    scikit-learn.org/stable/auto_examples/model_selection/plot_precision_recall.html
    Sat Aug 23 16:32:03 UTC 2025
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  3. Prediction Intervals for Gradient Boosting Regr...

    test datasets: X_train , X_test , y_train , y_test = train_test_split...( X_test , y_test , "b." , markersize = 10 , label = "Test observations"...
    scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_quantile.html
    Sat Aug 23 16:32:03 UTC 2025
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  4. Decision Tree Regression — scikit-learn 1.7.1 d...

    Get predictions on the test set X_test = np . arange ( 0.0 , 5.0...predict ( X_test ) y_2 = regr_2 . predict ( X_test ) Plot the...
    scikit-learn.org/stable/auto_examples/tree/plot_tree_regression.html
    Sat Aug 23 16:32:04 UTC 2025
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  5. Lagged features for time series forecasting — s...

    import train_test_split X_train , X_test , y_train , y_test = train_test_split...train_test_split ( X , y , test_size = 0.2 , random_state = 42 )...
    scikit-learn.org/stable/auto_examples/applications/plot_time_series_lagged_features.html
    Sat Aug 23 16:32:04 UTC 2025
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  6. Comparing Random Forests and Histogram Gradient...

    significant improvement of the testing score. Plot results # We can...elapsed computing time and mean test score. Passing the cursor over...
    scikit-learn.org/stable/auto_examples/ensemble/plot_forest_hist_grad_boosting_comparison.html
    Sat Aug 23 16:32:04 UTC 2025
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  7. MNIST classification using multinomial logistic...

    X_test , y_train , y_test = train_test_split ( X ,...( X_train ) X_test = scaler . transform ( X_test ) # Turn up tolerance...
    scikit-learn.org/stable/auto_examples/linear_model/plot_sparse_logistic_regression_mnist.html
    Sat Aug 23 16:32:03 UTC 2025
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  8. preprocessing.rst.txt

    X_test, y_train, y_test = train_test_split(X, y, random_state=42)...pipe.score(X_test, y_test) # apply scaling on testing data, without...
    scikit-learn.org/stable/_sources/modules/preprocessing.rst.txt
    Sat Aug 23 16:32:03 UTC 2025
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  9. plot_classifier_comparison.rst.txt

    and test part X, y = ds X_train, X_test, y_train, y_test = train_test_split(...Plot the testing points ax.scatter( X_test[:, 0], X_test[:, 1],...
    scikit-learn.org/stable/_sources/auto_examples/classification/plot_classifier_comparison.rst.txt
    Sat Aug 23 16:32:04 UTC 2025
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  10. Release Highlights for scikit-learn 1.5 — sciki...

    X_test , y_train , y_test = train_test_split ( X ,...from_estimator ( classifier_05 , X_test , y_test ) Lowering the threshold,...
    scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_5_0.html
    Sat Aug 23 16:32:03 UTC 2025
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