Eddie Bergman: Port over to AutoML common (#1318)

Author: Github Actions

development/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip

@@ -154,7 +154,7 @@ View the models found by auto-sklearn
 
               rank  ensemble_weight           type      cost  duration
     model_id                                                          
-    2            1              1.0  random_forest  0.447294  4.364232
+    2            1              1.0  random_forest  0.447294  4.122788
 
 
 
@@ -262,7 +262,7 @@ Get the Score of the final ensemble
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  16.939 seconds)
+   **Total running time of the script:** ( 0 minutes  15.843 seconds)
 
 
 .. _sphx_glr_download_examples_20_basic_example_multilabel_classification.py:

development/_downloads/fb625db3c50d423b1b7881136ffdeec8/examples_jupyter.zip

@@ -124,7 +124,7 @@ View the models found by auto-sklearn
 
               rank  ensemble_weight              type          cost  duration
     model_id                                                                 
-    18           1              1.0  gaussian_process  1.021347e-08  2.858771
+    12           1              1.0  gaussian_process  1.125731e-10  6.505112
 
 
 
@@ -151,7 +151,7 @@ Print the final ensemble constructed by auto-sklearn
 
  .. code-block:: none
 
-    [(1.000000, SimpleRegressionPipeline({'data_preprocessor:__choice__': 'feature_type', 'feature_preprocessor:__choice__': 'no_preprocessing', 'regressor:__choice__': 'gaussian_process', 'data_preprocessor:feature_type:categorical_transformer:categorical_encoding:__choice__': 'no_encoding', 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:__choice__': 'minority_coalescer', 'data_preprocessor:feature_type:numerical_transformer:imputation:strategy': 'median', 'data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__': 'none', 'regressor:gaussian_process:alpha': 6.862614540380134e-10, 'regressor:gaussian_process:thetaL': 1.944608422766674e-09, 'regressor:gaussian_process:thetaU': 917.8440681079683, 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction': 0.00018156864684755125},
+    [(1.000000, SimpleRegressionPipeline({'data_preprocessor:__choice__': 'feature_type', 'feature_preprocessor:__choice__': 'no_preprocessing', 'regressor:__choice__': 'gaussian_process', 'data_preprocessor:feature_type:categorical_transformer:categorical_encoding:__choice__': 'one_hot_encoding', 'data_preprocessor:feature_type:categorical_transformer:category_coalescence:__choice__': 'no_coalescense', 'data_preprocessor:feature_type:numerical_transformer:imputation:strategy': 'most_frequent', 'data_preprocessor:feature_type:numerical_transformer:rescaling:__choice__': 'minmax', 'regressor:gaussian_process:alpha': 5.779680060624107e-12, 'regressor:gaussian_process:thetaL': 1.1426676475875125e-10, 'regressor:gaussian_process:thetaU': 67194.35311216833},
     dataset_properties={
       'task': 5,
       'sparse': False,
@@ -186,7 +186,7 @@ Get the Score of the final ensemble
 
  .. code-block:: none
 
-    R2 score: 0.9999999870724605
+    R2 score: 0.9999999999006857
 
 
 
@@ -409,7 +409,7 @@ Get the configuration space
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  55.142 seconds)
+   **Total running time of the script:** ( 1 minutes  55.217 seconds)
 
 
 .. _sphx_glr_download_examples_20_basic_example_multioutput_regression.py:

development/_images/sphx_glr_example_inspect_predictions_002.png

@@ -121,11 +121,11 @@ View the models found by auto-sklearn
 
               rank  ensemble_weight               type      cost   duration
     model_id                                                               
-    25           1             0.46                sgd  0.436679   0.831828
-    6            2             0.32     ard_regression  0.455042   0.847448
-    27           3             0.14     ard_regression  0.462249   0.826625
-    11           4             0.02      random_forest  0.507400  10.825404
-    7            5             0.06  gradient_boosting  0.518673   1.553152
+    25           1             0.46                sgd  0.436679   0.752868
+    6            2             0.32     ard_regression  0.455042   0.802489
+    27           3             0.14     ard_regression  0.462249   0.785675
+    11           4             0.02      random_forest  0.507400  10.257058
+    7            5             0.06  gradient_boosting  0.518673   1.482558
 
 
 
@@ -267,7 +267,7 @@ the true value).
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 2 minutes  3.425 seconds)
+   **Total running time of the script:** ( 1 minutes  55.166 seconds)
 
 
 .. _sphx_glr_download_examples_20_basic_example_regression.py:

development/_images/sphx_glr_example_pandas_train_test_001.png

@@ -5,14 +5,14 @@
 
 Computation times
 =================
-**06:15.313** total execution time for **examples_20_basic** files:
+**06:07.703** total execution time for **examples_20_basic** files:
 
 +-------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_examples_20_basic_example_regression.py` (``example_regression.py``)                               | 02:03.425 | 0.0 MB |
+| :ref:`sphx_glr_examples_20_basic_example_classification.py` (``example_classification.py``)                       | 02:01.477 | 0.0 MB |
 +-------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_examples_20_basic_example_classification.py` (``example_classification.py``)                       | 01:59.808 | 0.0 MB |
+| :ref:`sphx_glr_examples_20_basic_example_multioutput_regression.py` (``example_multioutput_regression.py``)       | 01:55.217 | 0.0 MB |
 +-------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_examples_20_basic_example_multioutput_regression.py` (``example_multioutput_regression.py``)       | 01:55.142 | 0.0 MB |
+| :ref:`sphx_glr_examples_20_basic_example_regression.py` (``example_regression.py``)                               | 01:55.166 | 0.0 MB |
 +-------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_examples_20_basic_example_multilabel_classification.py` (``example_multilabel_classification.py``) | 00:16.939 | 0.0 MB |
+| :ref:`sphx_glr_examples_20_basic_example_multilabel_classification.py` (``example_multilabel_classification.py``) | 00:15.843 | 0.0 MB |
 +-------------------------------------------------------------------------------------------------------------------+-----------+--------+