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DummyClassifier — scikit-learn 1.7.2 docu...
score ( X , y ) 0.75 fit ( X , y ,...arithmetically, for each output. score ( X , y , sample_weight = None...scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyClassifier.html -
GammaRegressor — scikit-learn 1.7.2 docum...
score ( X , y ) np.float64(0.773)...(n_samples,) Returns predicted values. score ( X , y , sample_weight = None...scikit-learn.org/stable/modules/generated/sklearn.linear_model.GammaRegressor.html -
plot_hgbt_regression.zip
training if the validation score does not # improve (or degrades)..."categorical_features": None, "scoring": "neg_root_mean_squared_error",...scikit-learn.org/stable/_downloads/ef504a3cb245a55fde178198c8218b4a/plot_hgbt_regression.zip -
Gradient Boosting Out-of-Bag estimates — ...
score ( X_test , y_test ) print (..."""compute deviance scores on ``X_test`` and ``y_test...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_oob.html -
Comparison of Calibration of Classifiers —...
minimize proper scoring rules: the Brier score or the log-loss...- 6 , 6 , 101 ), cv = 10 , scoring = "neg_log_loss"...scikit-learn.org/stable/auto_examples/calibration/plot_compare_calibration.html -
Combine predictors using stacking — sciki...
time () scores = cross_validate ( est , X , y , scoring = list...seconds" ) for name , score in scores . items (): ax . plot ([],...scikit-learn.org/stable/auto_examples/ensemble/plot_stack_predictors.html -
TweedieRegressor — scikit-learn 1.7.2 doc...
score ( X , y ) np.float64(0.839)...(n_samples,) Returns predicted values. score ( X , y , sample_weight = None...scikit-learn.org/stable/modules/generated/sklearn.linear_model.TweedieRegressor.html -
MNIST classification using multinomial logistic...
coef_ == 0 ) * 100 score = clf . score ( X_test , y_test ) #..."Test score with L1 penalty: %.4f " % score ) coef =...scikit-learn.org/stable/auto_examples/linear_model/plot_sparse_logistic_regression_mnist.html -
Adjustment for chance in clustering performance...
scores . mean ( axis = 1 ), scores . std ( axis..., np . median ( scores , axis = 1 ), scores . std ( axis = 1...scikit-learn.org/stable/auto_examples/cluster/plot_adjusted_for_chance_measures.html -
Effect of varying threshold for self-training &...
scores . mean ( axis = 1 ), yerr = scores . std ( axis...append ( x_values , 0.99999 ) scores = np . empty (( x_values ....scikit-learn.org/stable/auto_examples/semi_supervised/plot_self_training_varying_threshold.html