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scikit-learn · Jan 14, 2025 · 6c80cdd · 6c80cdd
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diff --git a/dev/_downloads/02fe21a1f5d14bd1ebbe34aa905d9bf6/plot_multilabel.zip b/dev/_downloads/02fe21a1f5d14bd1ebbe34aa905d9bf6/plot_multilabel.zip
diff --git a/dev/_downloads/0358b1921962fd7c6f5a94c5abc91476/plot_hashing_vs_dict_vectorizer.zip b/dev/_downloads/0358b1921962fd7c6f5a94c5abc91476/plot_hashing_vs_dict_vectorizer.zip
diff --git a/dev/_downloads/038d1885eb5f5ea53aca42da3031fe38/plot_document_clustering.zip b/dev/_downloads/038d1885eb5f5ea53aca42da3031fe38/plot_document_clustering.zip
diff --git a/dev/_downloads/03c018a16384c69f3a89e473650d57ee/plot_svm_margin.zip b/dev/_downloads/03c018a16384c69f3a89e473650d57ee/plot_svm_margin.zip
diff --git a/dev/_downloads/04b9a7769df5b331f4d94e1d065b4311/plot_voting_decision_regions.zip b/dev/_downloads/04b9a7769df5b331f4d94e1d065b4311/plot_voting_decision_regions.zip
diff --git a/dev/_downloads/053b58bbfc8177072856c743b2c93424/plot_varimax_fa.zip b/dev/_downloads/053b58bbfc8177072856c743b2c93424/plot_varimax_fa.zip
diff --git a/dev/_downloads/06c18f4675ecd124f98537d05e10abd0/plot_nca_dim_reduction.zip b/dev/_downloads/06c18f4675ecd124f98537d05e10abd0/plot_nca_dim_reduction.zip
diff --git a/..._downloads/06e5cfec52777b1f220312b4ada9469d/plot_document_classification_20newsgroups.zip b/..._downloads/06e5cfec52777b1f220312b4ada9469d/plot_document_classification_20newsgroups.zip
diff --git a/dev/_downloads/07882f339cdda68a73e6335f34418af6/plot_theilsen.zip b/dev/_downloads/07882f339cdda68a73e6335f34418af6/plot_theilsen.zip
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diff --git a/dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip b/dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip
diff --git a/dev/_downloads/0919b8971cbb94ffb3b06c80621a3283/plot_label_propagation_structure.zip b/dev/_downloads/0919b8971cbb94ffb3b06c80621a3283/plot_label_propagation_structure.zip
diff --git a/dev/_downloads/0a3f5445678ab43e77a0d7602ce7e53a/plot_nca_illustration.zip b/dev/_downloads/0a3f5445678ab43e77a0d7602ce7e53a/plot_nca_illustration.zip
diff --git a/dev/_downloads/0afbdae4d5c21dfbf1e7f98e95e973c5/plot_separating_hyperplane.zip b/dev/_downloads/0afbdae4d5c21dfbf1e7f98e95e973c5/plot_separating_hyperplane.zip
diff --git a/dev/_downloads/0b03eb096c3d32195335ba930a0b3662/plot_digits_agglomeration.zip b/dev/_downloads/0b03eb096c3d32195335ba930a0b3662/plot_digits_agglomeration.zip
diff --git a/dev/_downloads/0b569e153dc27fb6eeb5063e271e8921/plot_rfe_digits.zip b/dev/_downloads/0b569e153dc27fb6eeb5063e271e8921/plot_rfe_digits.zip
diff --git a/dev/_downloads/1003e2b79d0fc902b8f0cbd0f449fd06/plot_birch_vs_minibatchkmeans.zip b/dev/_downloads/1003e2b79d0fc902b8f0cbd0f449fd06/plot_birch_vs_minibatchkmeans.zip
diff --git a/...wnloads/11651f4eebcf15ff7959e210e82dc45c/plot_linear_model_coefficient_interpretation.zip b/...wnloads/11651f4eebcf15ff7959e210e82dc45c/plot_linear_model_coefficient_interpretation.zip
diff --git a/dev/_downloads/1180cd432166ec9764125420df10ec77/plot_poisson_regression_non_normal_loss.zip b/dev/_downloads/1180cd432166ec9764125420df10ec77/plot_poisson_regression_non_normal_loss.zip
diff --git a/dev/_downloads/129e49615b0c1e7782384456dd7c3ec3/plot_rfe_with_cross_validation.zip b/dev/_downloads/129e49615b0c1e7782384456dd7c3ec3/plot_rfe_with_cross_validation.zip
diff --git a/dev/_downloads/12fb3a51f4f60a9be2386b10ccc076cf/plot_gpr_noisy.zip b/dev/_downloads/12fb3a51f4f60a9be2386b10ccc076cf/plot_gpr_noisy.zip
diff --git a/dev/_downloads/1393861b58df827d4c681b80a5be2472/plot_kmeans_digits.zip b/dev/_downloads/1393861b58df827d4c681b80a5be2472/plot_kmeans_digits.zip
diff --git a/dev/_downloads/151e78f803ff9f3154dd7dbbaf45e0b0/plot_release_highlights_1_6_0.zip b/dev/_downloads/151e78f803ff9f3154dd7dbbaf45e0b0/plot_release_highlights_1_6_0.zip
diff --git a/dev/_downloads/1548afe7d3147cdbff3b5cba88ffc124/plot_sparse_coding.zip b/dev/_downloads/1548afe7d3147cdbff3b5cba88ffc124/plot_sparse_coding.zip
diff --git a/dev/_downloads/161b401efba4b01936c9871f71688386/plot_species_kde.zip b/dev/_downloads/161b401efba4b01936c9871f71688386/plot_species_kde.zip
diff --git a/dev/_downloads/1630d9144544d31ca40f70d5ce894b1c/plot_roc_curve_visualization_api.zip b/dev/_downloads/1630d9144544d31ca40f70d5ce894b1c/plot_roc_curve_visualization_api.zip
diff --git a/dev/_downloads/175dc7cd79fedbe3d38829513430275a/plot_forest_importances.zip b/dev/_downloads/175dc7cd79fedbe3d38829513430275a/plot_forest_importances.zip
diff --git a/dev/_downloads/1929d77b217d252c180ea45cab60f1c0/plot_kmeans_assumptions.zip b/dev/_downloads/1929d77b217d252c180ea45cab60f1c0/plot_kmeans_assumptions.zip
diff --git a/dev/_downloads/1969c243dbe2c542ebd3887f2ecde211/plot_coin_ward_segmentation.zip b/dev/_downloads/1969c243dbe2c542ebd3887f2ecde211/plot_coin_ward_segmentation.zip
diff --git a/dev/_downloads/1acfe5256fc92dfaed2c1033304ed297/plot_gradient_boosting_regularization.zip b/dev/_downloads/1acfe5256fc92dfaed2c1033304ed297/plot_gradient_boosting_regularization.zip
diff --git a/dev/_downloads/1c8e15dadd5530db0ffab60f34a29a64/plot_discretization_classification.zip b/dev/_downloads/1c8e15dadd5530db0ffab60f34a29a64/plot_discretization_classification.zip
diff --git a/dev/_downloads/1c9575e30c88815f6de0280064b2c594/plot_missing_values.zip b/dev/_downloads/1c9575e30c88815f6de0280064b2c594/plot_missing_values.zip
diff --git a/dev/_downloads/1e308ad8f0f51110ea07c8d3b552c5bf/plot_pcr_vs_pls.zip b/dev/_downloads/1e308ad8f0f51110ea07c8d3b552c5bf/plot_pcr_vs_pls.zip
diff --git a/dev/_downloads/1e69769246e8d916462fd0c67f19c605/plot_set_output.zip b/dev/_downloads/1e69769246e8d916462fd0c67f19c605/plot_set_output.zip
diff --git a/dev/_downloads/1fffb175865f0e684095ddb70724914b/plot_release_highlights_1_5_0.zip b/dev/_downloads/1fffb175865f0e684095ddb70724914b/plot_release_highlights_1_5_0.zip
diff --git a/dev/_downloads/200e4f5a26d62475b041ec6d03eca0a6/plot_logistic_multinomial.zip b/dev/_downloads/200e4f5a26d62475b041ec6d03eca0a6/plot_logistic_multinomial.zip
diff --git a/dev/_downloads/207f6ccc40c29c40986fcdad2dcf463f/plot_digits_kde_sampling.zip b/dev/_downloads/207f6ccc40c29c40986fcdad2dcf463f/plot_digits_kde_sampling.zip
diff --git a/dev/_downloads/20976afc231c41d12cde1932ddd60594/plot_species_distribution_modeling.zip b/dev/_downloads/20976afc231c41d12cde1932ddd60594/plot_species_distribution_modeling.zip
diff --git a/dev/_downloads/20d4c73f80be097989f7cb73d3588767/plot_oneclass.zip b/dev/_downloads/20d4c73f80be097989f7cb73d3588767/plot_oneclass.zip
diff --git a/dev/_downloads/20f62896d2f883bba3587708f3e8a82a/plot_successive_halving_iterations.zip b/dev/_downloads/20f62896d2f883bba3587708f3e8a82a/plot_successive_halving_iterations.zip
diff --git a/dev/_downloads/2153fd2d9ab25873fb0a10316b24a9fe/plot_kmeans_plusplus.zip b/dev/_downloads/2153fd2d9ab25873fb0a10316b24a9fe/plot_kmeans_plusplus.zip
diff --git a/dev/_downloads/21a52befdcfce43d65a7b00dc6414056/plot_gpr_prior_posterior.zip b/dev/_downloads/21a52befdcfce43d65a7b00dc6414056/plot_gpr_prior_posterior.zip
diff --git a/dev/_downloads/21c126a0a1b9942f3e59abf4750774bc/plot_gmm_covariances.zip b/dev/_downloads/21c126a0a1b9942f3e59abf4750774bc/plot_gmm_covariances.zip
diff --git a/dev/_downloads/2216a33072e644eaf7be587530c2726d/plot_compare_calibration.zip b/dev/_downloads/2216a33072e644eaf7be587530c2726d/plot_compare_calibration.zip
diff --git a/dev/_downloads/235d8129d59e30e986be1e36b5badcc5/plot_monotonic_constraints.zip b/dev/_downloads/235d8129d59e30e986be1e36b5badcc5/plot_monotonic_constraints.zip
diff --git a/dev/_downloads/2393eac1ae8c3b57f87d3a992f256469/plot_det.zip b/dev/_downloads/2393eac1ae8c3b57f87d3a992f256469/plot_det.zip
diff --git a/dev/_downloads/248a4cae89eb02703d4ab8c58361c523/plot_likelihood_ratios.zip b/dev/_downloads/248a4cae89eb02703d4ab8c58361c523/plot_likelihood_ratios.zip
diff --git a/dev/_downloads/24e6ec210b28537f67bbf0b9a883e04b/plot_roc.zip b/dev/_downloads/24e6ec210b28537f67bbf0b9a883e04b/plot_roc.zip
diff --git a/dev/_downloads/250bd742eab59d3e4df845fe6c5fbaf4/plot_lda.zip b/dev/_downloads/250bd742eab59d3e4df845fe6c5fbaf4/plot_lda.zip
diff --git a/dev/_downloads/25110f74d039a8886ab72ea3a1c2876d/plot_digits_pipe.zip b/dev/_downloads/25110f74d039a8886ab72ea3a1c2876d/plot_digits_pipe.zip
diff --git a/dev/_downloads/26485aa00d25776ba2b4e87114e5ad56/plot_manifold_sphere.zip b/dev/_downloads/26485aa00d25776ba2b4e87114e5ad56/plot_manifold_sphere.zip
diff --git a/dev/_downloads/27381e4bd5a9b2476f7ed4a8c0d7c8a2/plot_release_highlights_1_3_0.zip b/dev/_downloads/27381e4bd5a9b2476f7ed4a8c0d7c8a2/plot_release_highlights_1_3_0.zip
diff --git a/dev/_downloads/27a581bf95a4c4534db079c70a1a14de/plot_f_test_vs_mi.zip b/dev/_downloads/27a581bf95a4c4534db079c70a1a14de/plot_f_test_vs_mi.zip
diff --git a/dev/_downloads/27a5c8b09da77b54a3849bd8e0ff0d31/plot_nnls.zip b/dev/_downloads/27a5c8b09da77b54a3849bd8e0ff0d31/plot_nnls.zip
diff --git a/dev/_downloads/2a405f4296fe09a86824e347e7ccf7e5/plot_discretization.zip b/dev/_downloads/2a405f4296fe09a86824e347e7ccf7e5/plot_discretization.zip
diff --git a/dev/_downloads/2b824c234439fb855e512d2465db9d8e/plot_scaling_importance.zip b/dev/_downloads/2b824c234439fb855e512d2465db9d8e/plot_scaling_importance.zip
diff --git a/dev/_downloads/2cb37d76ae6c02821275d6ef8b96620f/plot_ica_blind_source_separation.zip b/dev/_downloads/2cb37d76ae6c02821275d6ef8b96620f/plot_ica_blind_source_separation.zip
diff --git a/dev/_downloads/2d75858f1918f42d1d87ecc7a8cf141d/plot_sgd_comparison.zip b/dev/_downloads/2d75858f1918f42d1d87ecc7a8cf141d/plot_sgd_comparison.zip
diff --git a/dev/_downloads/2dd2f734250e8481fde18f8cd2e3820c/plot_target_encoder.zip b/dev/_downloads/2dd2f734250e8481fde18f8cd2e3820c/plot_target_encoder.zip
diff --git a/dev/_downloads/2e18b618565acbb9b5918136a879a534/plot_logistic_path.zip b/dev/_downloads/2e18b618565acbb9b5918136a879a534/plot_logistic_path.zip
diff --git a/dev/_downloads/2f1e361eb1d2ca997cf5da2e2651b7bb/plot_column_transformer.zip b/dev/_downloads/2f1e361eb1d2ca997cf5da2e2651b7bb/plot_column_transformer.zip
diff --git a/dev/_downloads/2f3ef774a6d7e52e1e6b7ccbb75d25f0/plot_gradient_boosting_quantile.py b/dev/_downloads/2f3ef774a6d7e52e1e6b7ccbb75d25f0/plot_gradient_boosting_quantile.py
@@ -104,12 +104,10 @@ def f(x):
 y_med = all_models["q 0.50"].predict(xx)
 
 fig = plt.figure(figsize=(10, 10))
-plt.plot(xx, f(xx), "g:", linewidth=3, label=r"$f(x) = x\,\sin(x)$")
+plt.plot(xx, f(xx), "black", linewidth=3, label=r"$f(x) = x\,\sin(x)$")
 plt.plot(X_test, y_test, "b.", markersize=10, label="Test observations")
-plt.plot(xx, y_med, "r-", label="Predicted median")
-plt.plot(xx, y_pred, "r-", label="Predicted mean")
-plt.plot(xx, y_upper, "k-")
-plt.plot(xx, y_lower, "k-")
+plt.plot(xx, y_med, "tab:orange", linewidth=3, label="Predicted median")
+plt.plot(xx, y_pred, "tab:green", linewidth=3, label="Predicted mean")
 plt.fill_between(
     xx.ravel(), y_lower, y_upper, alpha=0.4, label="Predicted 90% interval"
 )
@@ -310,10 +308,8 @@ def coverage_fraction(y, y_low, y_high):
 y_upper = search_95p.predict(xx)
 
 fig = plt.figure(figsize=(10, 10))
-plt.plot(xx, f(xx), "g:", linewidth=3, label=r"$f(x) = x\,\sin(x)$")
+plt.plot(xx, f(xx), "black", linewidth=3, label=r"$f(x) = x\,\sin(x)$")
 plt.plot(X_test, y_test, "b.", markersize=10, label="Test observations")
-plt.plot(xx, y_upper, "k-")
-plt.plot(xx, y_lower, "k-")
 plt.fill_between(
     xx.ravel(), y_lower, y_upper, alpha=0.4, label="Predicted 90% interval"
 )

diff --git a/dev/_downloads/2f60e3212e8896cf10a907dfe4a6a631/plot_gradient_boosting_quantile.zip b/dev/_downloads/2f60e3212e8896cf10a907dfe4a6a631/plot_gradient_boosting_quantile.zip
diff --git a/dev/_downloads/2f7b3682e03ebd7066495c3252414a44/plot_lasso_dense_vs_sparse_data.zip b/dev/_downloads/2f7b3682e03ebd7066495c3252414a44/plot_lasso_dense_vs_sparse_data.zip
diff --git a/...downloads/2f90cc6b2b011c5fa616a3a47c2ed8d1/plot_permutation_importance_multicollinear.zip b/...downloads/2f90cc6b2b011c5fa616a3a47c2ed8d1/plot_permutation_importance_multicollinear.zip
diff --git a/dev/_downloads/2fce81c38823a4c8e6cf7beebb010f00/plot_gradient_boosting_oob.zip b/dev/_downloads/2fce81c38823a4c8e6cf7beebb010f00/plot_gradient_boosting_oob.zip
diff --git a/dev/_downloads/3019a99f3f124514f9a0650bcb33fa27/plot_spectral_coclustering.zip b/dev/_downloads/3019a99f3f124514f9a0650bcb33fa27/plot_spectral_coclustering.zip
diff --git a/dev/_downloads/30cf609ec45ebd9e95d54912b37002fa/plot_lasso_lars_ic.zip b/dev/_downloads/30cf609ec45ebd9e95d54912b37002fa/plot_lasso_lars_ic.zip
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diff --git a/..._downloads/32b1787884d41cf7a0b36640001d381f/plot_permutation_tests_for_classification.zip b/..._downloads/32b1787884d41cf7a0b36640001d381f/plot_permutation_tests_for_classification.zip
diff --git a/dev/_downloads/3344592b61c45b04f094dd038d2e2efd/plot_column_transformer_mixed_types.zip b/dev/_downloads/3344592b61c45b04f094dd038d2e2efd/plot_column_transformer_mixed_types.zip
diff --git a/..._downloads/35620548aa1dcefbc9e36e7330feafdc/plot_forest_hist_grad_boosting_comparison.zip b/..._downloads/35620548aa1dcefbc9e36e7330feafdc/plot_forest_hist_grad_boosting_comparison.zip
diff --git a/dev/_downloads/35ddd809a204588ba5e0d93a2ac44682/plot_feature_union.zip b/dev/_downloads/35ddd809a204588ba5e0d93a2ac44682/plot_feature_union.zip
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diff --git a/dev/_downloads/388f5c580f2084392fb899ca1bc53867/plot_label_propagation_digits.zip b/dev/_downloads/388f5c580f2084392fb899ca1bc53867/plot_label_propagation_digits.zip
diff --git a/dev/_downloads/3a435b85c0a6eebd325c2b99faad732b/plot_swissroll.zip b/dev/_downloads/3a435b85c0a6eebd325c2b99faad732b/plot_swissroll.zip
diff --git a/dev/_downloads/3ad3d8de76dc79e282240ff9d4aec996/plot_causal_interpretation.zip b/dev/_downloads/3ad3d8de76dc79e282240ff9d4aec996/plot_causal_interpretation.zip
diff --git a/dev/_downloads/3d2c40ab2cfee918c269fd63cd2bc466/plot_model_complexity_influence.zip b/dev/_downloads/3d2c40ab2cfee918c269fd63cd2bc466/plot_model_complexity_influence.zip
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diff --git a/dev/_downloads/3d6718e20e6b7b05b7cdaa333a6d05a4/plot_bisect_kmeans.zip b/dev/_downloads/3d6718e20e6b7b05b7cdaa333a6d05a4/plot_bisect_kmeans.zip
diff --git a/dev/_downloads/3d67d60c4ffe2f928db30cd3174e5389/plot_ward_structured_vs_unstructured.zip b/dev/_downloads/3d67d60c4ffe2f928db30cd3174e5389/plot_ward_structured_vs_unstructured.zip
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diff --git a/dev/_downloads/3e3ff82825c1590c99d9a44b3a517f55/plot_multiclass_overview.zip b/dev/_downloads/3e3ff82825c1590c99d9a44b3a517f55/plot_multiclass_overview.zip
diff --git a/dev/_downloads/41475a5e6fc6360930267b5cd092c937/plot_classification.zip b/dev/_downloads/41475a5e6fc6360930267b5cd092c937/plot_classification.zip
diff --git a/dev/_downloads/4158158e379fe1c9e1700dd8a6125179/plot_pca_vs_fa_model_selection.zip b/dev/_downloads/4158158e379fe1c9e1700dd8a6125179/plot_pca_vs_fa_model_selection.zip
diff --git a/dev/_downloads/419245a165589a136566a555741c80e8/plot_gpr_on_structured_data.zip b/dev/_downloads/419245a165589a136566a555741c80e8/plot_gpr_on_structured_data.zip
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diff --git a/dev/_downloads/44ae219cc6359efae1cf5a6dc3e4b2e8/plot_rbf_parameters.zip b/dev/_downloads/44ae219cc6359efae1cf5a6dc3e4b2e8/plot_rbf_parameters.zip
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diff --git a/dev/_downloads/461290890e86d787be8ca355c3c65e4a/plot_svm_regression.zip b/dev/_downloads/461290890e86d787be8ca355c3c65e4a/plot_svm_regression.zip
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diff --git a/dev/_downloads/a687ddc099cdaf81b25dcd61b9cb7672/plot_inductive_clustering.zip b/dev/_downloads/a687ddc099cdaf81b25dcd61b9cb7672/plot_inductive_clustering.zip
diff --git a/dev/_downloads/a88ca03d46b8289eaed2fc08e505bee2/plot_grid_search_refit_callable.zip b/dev/_downloads/a88ca03d46b8289eaed2fc08e505bee2/plot_grid_search_refit_callable.zip
diff --git a/dev/_downloads/a9b380a057ec6333fd7e96273331a9b8/plot_semi_supervised_newsgroups.zip b/dev/_downloads/a9b380a057ec6333fd7e96273331a9b8/plot_semi_supervised_newsgroups.zip
diff --git a/dev/_downloads/aba5d73e169336038beb51608b748211/plot_linearsvc_support_vectors.zip b/dev/_downloads/aba5d73e169336038beb51608b748211/plot_linearsvc_support_vectors.zip
diff --git a/dev/_downloads/aff4193b21ef6ea0af509058be609d18/plot_kernel_ridge_regression.zip b/dev/_downloads/aff4193b21ef6ea0af509058be609d18/plot_kernel_ridge_regression.zip
diff --git a/dev/_downloads/b12810e5af9bfe7f99d2564c84262560/plot_coin_segmentation.zip b/dev/_downloads/b12810e5af9bfe7f99d2564c84262560/plot_coin_segmentation.zip
diff --git a/dev/_downloads/b327cd0a0802e17daefbd5de7ade2705/plot_svm_scale_c.zip b/dev/_downloads/b327cd0a0802e17daefbd5de7ade2705/plot_svm_scale_c.zip
diff --git a/dev/_downloads/b55408ba1cd122d5939c6ec627dc6a10/plot_time_series_lagged_features.zip b/dev/_downloads/b55408ba1cd122d5939c6ec627dc6a10/plot_time_series_lagged_features.zip
diff --git a/dev/_downloads/b5ac5dfd67b0aab146fcb9faaac8480c/plot_gradient_boosting_quantile.ipynb b/dev/_downloads/b5ac5dfd67b0aab146fcb9faaac8480c/plot_gradient_boosting_quantile.ipynb
@@ -141,7 +141,7 @@
       },
       "outputs": [],
       "source": [
-        "import matplotlib.pyplot as plt\n\ny_pred = all_models[\"mse\"].predict(xx)\ny_lower = all_models[\"q 0.05\"].predict(xx)\ny_upper = all_models[\"q 0.95\"].predict(xx)\ny_med = all_models[\"q 0.50\"].predict(xx)\n\nfig = plt.figure(figsize=(10, 10))\nplt.plot(xx, f(xx), \"g:\", linewidth=3, label=r\"$f(x) = x\\,\\sin(x)$\")\nplt.plot(X_test, y_test, \"b.\", markersize=10, label=\"Test observations\")\nplt.plot(xx, y_med, \"r-\", label=\"Predicted median\")\nplt.plot(xx, y_pred, \"r-\", label=\"Predicted mean\")\nplt.plot(xx, y_upper, \"k-\")\nplt.plot(xx, y_lower, \"k-\")\nplt.fill_between(\n    xx.ravel(), y_lower, y_upper, alpha=0.4, label=\"Predicted 90% interval\"\n)\nplt.xlabel(\"$x$\")\nplt.ylabel(\"$f(x)$\")\nplt.ylim(-10, 25)\nplt.legend(loc=\"upper left\")\nplt.show()"
+        "import matplotlib.pyplot as plt\n\ny_pred = all_models[\"mse\"].predict(xx)\ny_lower = all_models[\"q 0.05\"].predict(xx)\ny_upper = all_models[\"q 0.95\"].predict(xx)\ny_med = all_models[\"q 0.50\"].predict(xx)\n\nfig = plt.figure(figsize=(10, 10))\nplt.plot(xx, f(xx), \"black\", linewidth=3, label=r\"$f(x) = x\\,\\sin(x)$\")\nplt.plot(X_test, y_test, \"b.\", markersize=10, label=\"Test observations\")\nplt.plot(xx, y_med, \"tab:orange\", linewidth=3, label=\"Predicted median\")\nplt.plot(xx, y_pred, \"tab:green\", linewidth=3, label=\"Predicted mean\")\nplt.fill_between(\n    xx.ravel(), y_lower, y_upper, alpha=0.4, label=\"Predicted 90% interval\"\n)\nplt.xlabel(\"$x$\")\nplt.ylabel(\"$f(x)$\")\nplt.ylim(-10, 25)\nplt.legend(loc=\"upper left\")\nplt.show()"
       ]
     },
     {
@@ -267,7 +267,7 @@
       },
       "outputs": [],
       "source": [
-        "y_lower = search_05p.predict(xx)\ny_upper = search_95p.predict(xx)\n\nfig = plt.figure(figsize=(10, 10))\nplt.plot(xx, f(xx), \"g:\", linewidth=3, label=r\"$f(x) = x\\,\\sin(x)$\")\nplt.plot(X_test, y_test, \"b.\", markersize=10, label=\"Test observations\")\nplt.plot(xx, y_upper, \"k-\")\nplt.plot(xx, y_lower, \"k-\")\nplt.fill_between(\n    xx.ravel(), y_lower, y_upper, alpha=0.4, label=\"Predicted 90% interval\"\n)\nplt.xlabel(\"$x$\")\nplt.ylabel(\"$f(x)$\")\nplt.ylim(-10, 25)\nplt.legend(loc=\"upper left\")\nplt.title(\"Prediction with tuned hyper-parameters\")\nplt.show()"
+        "y_lower = search_05p.predict(xx)\ny_upper = search_95p.predict(xx)\n\nfig = plt.figure(figsize=(10, 10))\nplt.plot(xx, f(xx), \"black\", linewidth=3, label=r\"$f(x) = x\\,\\sin(x)$\")\nplt.plot(X_test, y_test, \"b.\", markersize=10, label=\"Test observations\")\nplt.fill_between(\n    xx.ravel(), y_lower, y_upper, alpha=0.4, label=\"Predicted 90% interval\"\n)\nplt.xlabel(\"$x$\")\nplt.ylabel(\"$f(x)$\")\nplt.ylim(-10, 25)\nplt.legend(loc=\"upper left\")\nplt.title(\"Prediction with tuned hyper-parameters\")\nplt.show()"
       ]
     },
     {