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Results 361 - 380 of 1,271 for test (0.34 sec)

  1. 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
    Wed Nov 05 14:36:35 UTC 2025
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  2. Comparison of kernel ridge regression and SVR —...

    train_time = [] test_time = [] for train_test_size in sizes :...fit ( X [: train_test_size ], y [: train_test_size ]) train_time...
    scikit-learn.org/stable/auto_examples/miscellaneous/plot_kernel_ridge_regression.html
    Wed Nov 05 14:36:32 UTC 2025
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  3. Time-related feature engineering — scikit-learn...

    test_0 = all_splits [ 0 ] X . iloc [ test_0 ] season...train_4 , test_4 = all_splits [ 4 ] X . iloc [ test_4 ] season...
    scikit-learn.org/stable/auto_examples/applications/plot_cyclical_feature_engineering.html
    Wed Nov 05 14:36:33 UTC 2025
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  4. MultiTaskLassoCV — scikit-learn 1.7.2 documenta...

    default=None Values of alphas to test along the regularization path....An iterable yielding (train, test) splits as arrays of indices....
    scikit-learn.org/stable/modules/generated/sklearn.linear_model.MultiTaskLassoCV.html
    Wed Nov 05 14:36:32 UTC 2025
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  5. Overview of multiclass training meta-estimators...

    examples Nested versus non-nested cross-validation Nested versus..."DecisionTreeClassifi" : cv_results_tree [ "test_score" ], "OneVsOneClassifier"...
    scikit-learn.org/stable/auto_examples/multiclass/plot_multiclass_overview.html
    Wed Nov 05 14:36:33 UTC 2025
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  6. Prediction Latency — scikit-learn 1.7.2 documen...

    X_test , y_train , y_test = train_test_split ( X ,..., X_test , y_test = generate_dataset ( n_train , n_test , n )...
    scikit-learn.org/stable/auto_examples/applications/plot_prediction_latency.html
    Wed Nov 05 14:36:33 UTC 2025
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  7. 7.1. Pipelines and composite estimators — sciki...

    X_test , y_train , y_test = train_test_split ( X ,...score: { regr . score ( X_test , y_test ) : .2f } " ) R2 score:...
    scikit-learn.org/stable/modules/compose.html
    Wed Nov 05 14:36:33 UTC 2025
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  8. Precision-Recall — scikit-learn 1.7.2 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
    Wed Nov 05 14:36:32 UTC 2025
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  9. Comparing Target Encoder with Other Encoders — ...

    "rmse_test_mean" : rmse_test_score . mean (), "rmse_test_std"...= True , ) rmse_test_score = - result [ "test_score" ] rmse_train_score...
    scikit-learn.org/stable/auto_examples/preprocessing/plot_target_encoder.html
    Wed Nov 05 14:36:33 UTC 2025
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  10. 11. Common pitfalls and recommended practices —...

    X_test , y_train , y_test = train_test_split ( ......X_train , X_test , y_train , y_test = train_test_split ( ......
    scikit-learn.org/stable/common_pitfalls.html
    Wed Nov 05 14:36:35 UTC 2025
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  11. 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
    Wed Nov 05 14:36:35 UTC 2025
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  12. MNIST classification using multinomial logistic...

    X_test , y_train , y_test = train_test_split ( X ,...clf . score ( X_test , y_test ) # print('Best C % .4f' % clf.C_)...
    scikit-learn.org/stable/auto_examples/linear_model/plot_sparse_logistic_regression_mnist.html
    Wed Nov 05 14:36:32 UTC 2025
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  13. Getting Started — scikit-learn 1.7.2 documentation

    X_test , y_train , y_test = train_test_split ( X ,...X_train , X_test , y_train , y_test = train_test_split ( X ,...
    scikit-learn.org/stable/getting_started.html
    Wed Nov 05 14:36:33 UTC 2025
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  14. PredefinedSplit — scikit-learn 1.7.2 documentation

    Provides train/test indices to split data into train/test sets using...The entry test_fold[i] represents the index of the test set that...
    scikit-learn.org/stable/modules/generated/sklearn.model_selection.PredefinedSplit.html
    Wed Nov 05 14:36:35 UTC 2025
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  15. maihamadb properties

    test.prefix Env Lang Property uq Comment - - [Test] 1 The...to show test environment or not integration - [Test] 1 The prefix...
    dbflute.seasar.org/ja/data/doc/harbor/properties-maihamadb.html
    Mon Sep 15 10:51:15 UTC 2025
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  16. Underfitting vs. Overfitting — scikit-learn 1.7...

    plot ( X_test , pipeline . predict ( X_test [:, np . newaxis..."Model" ) plt . plot ( X_test , true_fun ( X_test ), label = "True function"...
    scikit-learn.org/stable/auto_examples/model_selection/plot_underfitting_overfitting.html
    Wed Nov 05 14:36:35 UTC 2025
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  17. Introducing the set_output API — scikit-learn 1...

    X_test , y_train , y_test = train_test_split ( X ,...X_train ) X_test_scaled = scaler . transform ( X_test ) X_test_scaled...
    scikit-learn.org/stable/auto_examples/miscellaneous/plot_set_output.html
    Wed Nov 05 14:36:32 UTC 2025
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  18. DBFlute Example (サンプル) | DBFlute

    MySQL dbflute-test-dbms-mysql PostgreSQL dbflute-test-dbms-postgresql...Oracle dbflute-test-dbms-oracle DB2 dbflute-test-dbms-db2 SQLServer...
    dbflute.seasar.org/ja/manual/reference/example/index.html
    Mon Sep 15 10:51:18 UTC 2025
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  19. Face completion with a multi-output estimators ...

    randint ( test . shape [ 0 ], size = ( n_faces ,)) test = test [ face_ids...2 :] X_test = test [:, : ( n_pixels + 1 ) // 2 ] y_test = test...
    scikit-learn.org/stable/auto_examples/miscellaneous/plot_multioutput_face_completion.html
    Wed Nov 05 14:36:32 UTC 2025
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  20. Probability calibration of classifiers — scikit...

    y_test , sw_train , sw_test = train_test_split ( X , y , sample_weight...split train, test for calibration X_train , X_test , y_train ,...
    scikit-learn.org/stable/auto_examples/calibration/plot_calibration.html
    Wed Nov 05 14:36:35 UTC 2025
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