Eddie Bergman: Cleanup of simple_imputer (#346)

Author: Github Actions

development/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip

@@ -86,13 +86,12 @@ Image Classification
      ________________________________________ 
     Configuration:
       image_augmenter:GaussianBlur:use_augmenter, Value: False
-      image_augmenter:GaussianNoise:sigma_offset, Value: 0.34378220529402603
-      image_augmenter:GaussianNoise:use_augmenter, Value: True
+      image_augmenter:GaussianNoise:use_augmenter, Value: False
       image_augmenter:RandomAffine:use_augmenter, Value: False
-      image_augmenter:RandomCutout:p, Value: 0.6073713136709832
+      image_augmenter:RandomCutout:p, Value: 0.5876458962649975
       image_augmenter:RandomCutout:use_augmenter, Value: True
       image_augmenter:Resize:use_augmenter, Value: True
-      image_augmenter:ZeroPadAndCrop:percent, Value: 0.4430360788212591
+      image_augmenter:ZeroPadAndCrop:percent, Value: 0.2913850064337656
       normalizer:__choice__, Value: 'NoNormalizer'
 
     Fitting the pipeline...
@@ -172,7 +171,7 @@ Image Classification
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  6.062 seconds)
+   **Total running time of the script:** ( 0 minutes  8.272 seconds)
 
 
 .. _sphx_glr_download_examples_20_basics_example_image_classification.py:

development/_downloads/fb625db3c50d423b1b7881136ffdeec8/examples_jupyter.zip

@@ -134,7 +134,7 @@ Search for an ensemble of machine learning algorithms
  .. code-block:: none
 
 
-    <autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7fc43748c250>
+    <autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7fa1ebe161c0>
 
 
 
@@ -199,7 +199,7 @@ Print the final ensemble performance
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 5 minutes  33.865 seconds)
+   **Total running time of the script:** ( 5 minutes  41.582 seconds)
 
 
 .. _sphx_glr_download_examples_20_basics_example_tabular_classification.py:

development/_images/sphx_glr_example_plot_over_time_001.png

@@ -125,7 +125,7 @@ Search for an ensemble of machine learning algorithms
  .. code-block:: none
 
 
-    <autoPyTorch.api.tabular_regression.TabularRegressionTask object at 0x7fc4d14de7f0>
+    <autoPyTorch.api.tabular_regression.TabularRegressionTask object at 0x7fa2860e07f0>
 
 
 
@@ -167,7 +167,7 @@ Print the final ensemble performance
     |  2 | None                                                              | LGBMLearner                                                     |     0.08 |
     |  3 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential |     0.06 |
     autoPyTorch results:
-            Dataset name: 1a250723-52c8-11ec-8713-0d74af095cbd
+            Dataset name: 293890d1-52ca-11ec-86ac-abb2a4e803bd
             Optimisation Metric: r2
             Best validation score: 0.8644967965917701
             Number of target algorithm runs: 24
@@ -183,7 +183,7 @@ Print the final ensemble performance
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 5 minutes  37.231 seconds)
+   **Total running time of the script:** ( 5 minutes  32.482 seconds)
 
 
 .. _sphx_glr_download_examples_20_basics_example_tabular_regression.py:

development/_images/sphx_glr_example_plot_over_time_thumb.png

@@ -5,12 +5,12 @@
 
 Computation times
 =================
-**11:17.159** total execution time for **examples_20_basics** files:
+**11:22.336** total execution time for **examples_20_basics** files:
 
 +--------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_examples_20_basics_example_tabular_regression.py` (``example_tabular_regression.py``)         | 05:37.231 | 0.0 MB |
+| :ref:`sphx_glr_examples_20_basics_example_tabular_classification.py` (``example_tabular_classification.py``) | 05:41.582 | 0.0 MB |
 +--------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_examples_20_basics_example_tabular_classification.py` (``example_tabular_classification.py``) | 05:33.865 | 0.0 MB |
+| :ref:`sphx_glr_examples_20_basics_example_tabular_regression.py` (``example_tabular_regression.py``)         | 05:32.482 | 0.0 MB |
 +--------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_examples_20_basics_example_image_classification.py` (``example_image_classification.py``)     | 00:06.062 | 0.0 MB |
+| :ref:`sphx_glr_examples_20_basics_example_image_classification.py` (``example_image_classification.py``)     | 00:08.272 | 0.0 MB |
 +--------------------------------------------------------------------------------------------------------------+-----------+--------+