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Nearest Neighbors Classification — scikit-learn...
X_test , y_train , y_test = train_test_split ( X ,...split the data into a train and test dataset. from sklearn.datasets...scikit-learn.org/stable/auto_examples/neighbors/plot_classification.html -
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 -
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 -
Decision Tree Regression — scikit-learn 1.5.0 d...
predict ( X_test ) y_2 = regr_2 . predict ( X_test ) # Plot the.... fit ( X , y ) # Predict X_test = np . arange ( 0.0 , 5.0 ,...scikit-learn.org/stable/auto_examples/tree/plot_tree_regression.html -
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 -
6.1. Pipelines and composite estimators — sciki...
X_test , y_train , y_test = train_test_split ( X ,...format ( regr . score ( X_test , y_test ))) R2 score: 0.61 >>> raw_target_regr...scikit-learn.org/stable/modules/compose.html -
UTFluteのセットアップ | DBFlute
@Java /** * The test case with container for unit test. * @author...PlainTestCase { public void test_demo() { // メソッド名が test で始まること markHere(...dbflute.seasar.org/ja/manual/function/helper/utflute/setup.html -
CalibratedClassifierCV — scikit-learn 1.5.0 doc...
and calibrates it using the testing subset. For prediction, predicted...An iterable yielding (train, test) splits as arrays of indices....scikit-learn.org/stable/modules/generated/sklearn.calibration.CalibratedClassifierCV.html -
Underfitting vs. Overfitting — scikit-learn 1.5...
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 -
plot_multi_metric_evaluation.py
``'_<scorer_name>'`` (``'mean_test_precision'``, ``'rank_test_precision'``, etc...)...style in (("train", "--"), ("test", "-")): sample_score_mean =...scikit-learn.org/stable/_downloads/dedbcc9464f3269f4f012f4bfc7d16da/plot_multi_metric_evaluation.py