.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "checks_gallery/tabular/performance/plot_regression_error_distribution.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_checks_gallery_tabular_performance_plot_regression_error_distribution.py: Regression Error Distribution ***************************** .. GENERATED FROM PYTHON SOURCE LINES 8-10 Imports ======= .. GENERATED FROM PYTHON SOURCE LINES 10-18 .. code-block:: default from sklearn.datasets import load_diabetes from sklearn.ensemble import GradientBoostingRegressor from sklearn.model_selection import train_test_split from deepchecks.tabular import Dataset from deepchecks.tabular.checks.performance import RegressionErrorDistribution .. GENERATED FROM PYTHON SOURCE LINES 19-21 Generating data =============== .. GENERATED FROM PYTHON SOURCE LINES 21-31 .. code-block:: default diabetes_df = load_diabetes(return_X_y=False, as_frame=True).frame train_df, test_df = train_test_split(diabetes_df, test_size=0.33, random_state=42) train = Dataset(train_df, label='target', cat_features=['sex']) test = Dataset(test_df, label='target', cat_features=['sex']) clf = GradientBoostingRegressor(random_state=0) _ = clf.fit(train.data[train.features], train.data[train.label_name]) .. GENERATED FROM PYTHON SOURCE LINES 32-34 Running RegressionErrorDistribution check (normal distribution) =============================================================== .. GENERATED FROM PYTHON SOURCE LINES 34-37 .. code-block:: default check = RegressionErrorDistribution() .. GENERATED FROM PYTHON SOURCE LINES 38-41 .. code-block:: default check.run(test, clf) .. raw:: html

Regression Error Distribution

Check regression error distribution.

Additional Outputs
Largest over estimation errors:
  age sex bmi bp s1 s2 s3 s4 s5 s6 target predicted target target Prediction Difference
364 0.00 0.05 -0.01 -0.02 -0.01 0.00 -0.04 0.03 0.01 0.10 262.00 120.59 141.41
9 -0.07 -0.04 0.04 -0.03 -0.01 -0.03 -0.02 -0.00 0.07 -0.01 310.00 183.63 126.37
77 -0.10 -0.04 -0.04 -0.07 -0.04 -0.03 0.02 -0.04 -0.07 -0.00 200.00 85.48 114.52
Largest under estimation errors:
  age sex bmi bp s1 s2 s3 s4 s5 s6 target predicted target target Prediction Difference
380 0.02 -0.04 0.03 0.06 -0.06 -0.04 -0.01 -0.03 -0.05 -0.03 52.00 223.72 -171.72
56 -0.04 -0.04 0.04 -0.03 -0.03 -0.03 -0.04 0.00 0.03 -0.02 52.00 199.97 -147.97
7 0.06 0.05 -0.00 0.07 0.09 0.11 0.02 0.02 -0.04 0.00 63.00 183.45 -120.45


.. GENERATED FROM PYTHON SOURCE LINES 42-44 Skewing the data ---------------- .. GENERATED FROM PYTHON SOURCE LINES 44-47 .. code-block:: default test.data[test.label_name] = 150 .. GENERATED FROM PYTHON SOURCE LINES 48-50 Running RegressionErrorDistribution check (abnormal distribution) ================================================================= .. GENERATED FROM PYTHON SOURCE LINES 50-53 .. code-block:: default check = RegressionErrorDistribution() .. GENERATED FROM PYTHON SOURCE LINES 54-56 .. code-block:: default check.run(test, clf) .. raw:: html

Regression Error Distribution

Check regression error distribution.

Additional Outputs
Largest over estimation errors:
  age sex bmi bp s1 s2 s3 s4 s5 s6 target predicted target target Prediction Difference
237 0.06 -0.04 -0.07 -0.07 -0.00 -0.00 0.04 -0.04 -0.05 -0.00 150 59.07 90.93
436 -0.06 -0.04 -0.07 -0.05 -0.02 -0.05 0.09 -0.08 -0.06 -0.05 150 61.05 88.95
55 -0.04 -0.04 -0.05 -0.04 -0.01 -0.02 0.09 -0.04 -0.07 0.01 150 61.54 88.46
Largest under estimation errors:
  age sex bmi bp s1 s2 s3 s4 s5 s6 target predicted target target Prediction Difference
114 0.02 -0.04 0.11 0.06 0.01 -0.03 -0.02 0.02 0.10 0.02 150 302.13 -152.13
332 0.03 -0.04 0.10 0.08 -0.01 -0.01 -0.06 0.03 0.06 0.04 150 295.71 -145.71
321 0.10 -0.04 0.05 0.08 0.05 0.04 -0.08 0.14 0.10 0.06 150 269.18 -119.18


.. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 0.193 seconds) .. _sphx_glr_download_checks_gallery_tabular_performance_plot_regression_error_distribution.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_regression_error_distribution.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_regression_error_distribution.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_