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Ravin Kohli: Update README.md with link for master branch
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20 changes: 10 additions & 10 deletions development/_sources/examples/20_basics/example_image_classification.rst.txt
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Expand Up @@ -87,23 +87,23 @@ Image Classification
Configuration:
image_augmenter:GaussianBlur:use_augmenter, Value: False
image_augmenter:GaussianNoise:use_augmenter, Value: False
image_augmenter:RandomAffine:rotate, Value: 339
image_augmenter:RandomAffine:scale_offset, Value: 0.3007791010350451
image_augmenter:RandomAffine:shear, Value: 26
image_augmenter:RandomAffine:translate_percent_offset, Value: 0.03882945703151322
image_augmenter:RandomAffine:rotate, Value: 65
image_augmenter:RandomAffine:scale_offset, Value: 0.10364752234694663
image_augmenter:RandomAffine:shear, Value: 5
image_augmenter:RandomAffine:translate_percent_offset, Value: 0.12303023778688212
image_augmenter:RandomAffine:use_augmenter, Value: True
image_augmenter:RandomCutout:p, Value: 0.2663596033164267
image_augmenter:RandomCutout:p, Value: 0.9516838776905963
image_augmenter:RandomCutout:use_augmenter, Value: True
image_augmenter:Resize:use_augmenter, Value: True
image_augmenter:ZeroPadAndCrop:percent, Value: 0.39730616568269495
normalizer:__choice__, Value: 'NoNormalizer'
image_augmenter:Resize:use_augmenter, Value: False
image_augmenter:ZeroPadAndCrop:percent, Value: 0.2732380932749452
normalizer:__choice__, Value: 'ImageNormalizer'

Fitting the pipeline...
________________________________________
ImageClassificationPipeline
________________________________________
0-) normalizer:
NoNormalizer
ImageNormalizer

1-) preprocessing:
EarlyPreprocessing
Expand Down Expand Up @@ -175,7 +175,7 @@ Image Classification
.. rst-class:: sphx-glr-timing

**Total running time of the script:** ( 0 minutes 8.173 seconds)
**Total running time of the script:** ( 0 minutes 6.216 seconds)


.. _sphx_glr_download_examples_20_basics_example_image_classification.py:
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34 changes: 16 additions & 18 deletions development/_sources/examples/20_basics/example_tabular_classification.rst.txt
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Expand Up @@ -134,7 +134,7 @@ Search for an ensemble of machine learning algorithms
.. code-block:: none
<autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f81756dd610>
<autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f2f6f8c4940>
Expand Down Expand Up @@ -165,28 +165,26 @@ Print the final ensemble performance

.. code-block:: none
{'accuracy': 0.838150289017341}
| | Preprocessing | Estimator | Weight |
|---:|:------------------------------------------------------------------|:----------------------------------------------------------------|---------:|
| 0 | SimpleImputer,OneHotEncoder,Normalizer,KernelPCA | embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.2 |
| 1 | None | KNNLearner | 0.16 |
| 2 | None | CBLearner | 0.14 |
| 3 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.12 |
| 4 | SimpleImputer,OneHotEncoder,Normalizer,PowerTransformer | embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.08 |
| 5 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.08 |
| 6 | SimpleImputer,OneHotEncoder,MinMaxScaler,PowerTransformer | embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
| 7 | SimpleImputer,NoEncoder,Normalizer,Nystroem | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
| 8 | None | SVMLearner | 0.04 |
| 9 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
| 10 | SimpleImputer,OneHotEncoder,MinMaxScaler,TruncSVD | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
{'accuracy': 0.8554913294797688}
| | Preprocessing | Estimator | Weight |
|---:|:----------------------------------------------------------|:----------------------------------------------------------------|---------:|
| 0 | None | RFLearner | 0.24 |
| 1 | SimpleImputer,OneHotEncoder,Normalizer,KernelPCA | embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.22 |
| 2 | None | SVMLearner | 0.18 |
| 3 | None | CBLearner | 0.1 |
| 4 | None | ETLearner | 0.08 |
| 5 | None | KNNLearner | 0.08 |
| 6 | SimpleImputer,OneHotEncoder,MinMaxScaler,PowerTransformer | embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
| 7 | SimpleImputer,NoEncoder,Normalizer,Nystroem | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
| 8 | None | LGBMLearner | 0.02 |
autoPyTorch results:
Dataset name: Australian
Optimisation Metric: accuracy
Best validation score: 0.8713450292397661
Number of target algorithm runs: 22
Number of target algorithm runs: 23
Number of successful target algorithm runs: 19
Number of crashed target algorithm runs: 2
Number of target algorithms that exceeded the time limit: 1
Number of target algorithms that exceeded the time limit: 2
Number of target algorithms that exceeded the memory limit: 0
Expand All @@ -196,7 +194,7 @@ Print the final ensemble performance
.. rst-class:: sphx-glr-timing

**Total running time of the script:** ( 5 minutes 35.112 seconds)
**Total running time of the script:** ( 5 minutes 22.150 seconds)


.. _sphx_glr_download_examples_20_basics_example_tabular_classification.py:
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10 changes: 5 additions & 5 deletions development/_sources/examples/20_basics/example_tabular_regression.rst.txt
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Expand Up @@ -125,7 +125,7 @@ Search for an ensemble of machine learning algorithms
.. code-block:: none
<autoPyTorch.api.tabular_regression.TabularRegressionTask object at 0x7f8217ed1ca0>
<autoPyTorch.api.tabular_regression.TabularRegressionTask object at 0x7f30125fdca0>
Expand Down Expand Up @@ -159,17 +159,17 @@ Print the final ensemble performance

.. code-block:: none
{'r2': 0.944631023189658}
{'r2': 0.9445248186059718}
| | Preprocessing | Estimator | Weight |
|---:|:------------------------------------------------------------------|:----------------------------------------------------------------|---------:|
| 0 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.44 |
| 1 | None | CBLearner | 0.42 |
| 2 | None | LGBMLearner | 0.08 |
| 3 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
autoPyTorch results:
Dataset name: e0ac8c9c-4bbd-11ec-870e-7746ea156edb
Dataset name: 2b8bcd39-4bc0-11ec-8727-df8c3c818998
Optimisation Metric: r2
Best validation score: 0.8644967965917701
Best validation score: 0.8645385039886702
Number of target algorithm runs: 24
Number of successful target algorithm runs: 20
Number of crashed target algorithm runs: 2
Expand All @@ -183,7 +183,7 @@ Print the final ensemble performance
.. rst-class:: sphx-glr-timing

**Total running time of the script:** ( 5 minutes 34.172 seconds)
**Total running time of the script:** ( 5 minutes 37.415 seconds)


.. _sphx_glr_download_examples_20_basics_example_tabular_regression.py:
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8 changes: 4 additions & 4 deletions development/_sources/examples/20_basics/sg_execution_times.rst.txt
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Expand Up @@ -5,12 +5,12 @@

Computation times
=================
**11:17.457** total execution time for **examples_20_basics** files:
**11:05.781** total execution time for **examples_20_basics** files:

+--------------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_examples_20_basics_example_tabular_classification.py` (``example_tabular_classification.py``) | 05:35.112 | 0.0 MB |
| :ref:`sphx_glr_examples_20_basics_example_tabular_regression.py` (``example_tabular_regression.py``) | 05:37.415 | 0.0 MB |
+--------------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_examples_20_basics_example_tabular_regression.py` (``example_tabular_regression.py``) | 05:34.172 | 0.0 MB |
| :ref:`sphx_glr_examples_20_basics_example_tabular_classification.py` (``example_tabular_classification.py``) | 05:22.150 | 0.0 MB |
+--------------------------------------------------------------------------------------------------------------+-----------+--------+
| :ref:`sphx_glr_examples_20_basics_example_image_classification.py` (``example_image_classification.py``) | 00:08.173 | 0.0 MB |
| :ref:`sphx_glr_examples_20_basics_example_image_classification.py` (``example_image_classification.py``) | 00:06.216 | 0.0 MB |
+--------------------------------------------------------------------------------------------------------------+-----------+--------+
52 changes: 25 additions & 27 deletions ...opment/_sources/examples/40_advanced/example_custom_configuration_space.rst.txt
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Expand Up @@ -46,44 +46,42 @@ the search. Currently, there are two changes that can be made to the space:-

.. code-block:: none
{'accuracy': 0.8670520231213873}
{'accuracy': 0.8554913294797688}
| | Preprocessing | Estimator | Weight |
|---:|:------------------------------------------------------------------|:----------------------------------------------------------|---------:|
| 0 | None | RFLearner | 0.44 |
| 1 | None | ETLearner | 0.26 |
| 2 | None | LGBMLearner | 0.1 |
| 3 | None | SVMLearner | 0.08 |
| 4 | None | KNNLearner | 0.08 |
| 5 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
| 6 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
| 0 | None | CBLearner | 0.46 |
| 1 | SimpleImputer,OneHotEncoder,Normalizer,PolynomialFeatures | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.38 |
| 2 | None | SVMLearner | 0.06 |
| 3 | None | KNNLearner | 0.06 |
| 4 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
autoPyTorch results:
Dataset name: 4064d3b1-4bc2-11ec-870e-7746ea156edb
Dataset name: 85726e36-4bc4-11ec-8727-df8c3c818998
Optimisation Metric: accuracy
Best validation score: 0.8596491228070176
Number of target algorithm runs: 17
Number of successful target algorithm runs: 11
Number of crashed target algorithm runs: 5
Best validation score: 0.8654970760233918
Number of target algorithm runs: 18
Number of successful target algorithm runs: 14
Number of crashed target algorithm runs: 3
Number of target algorithms that exceeded the time limit: 1
Number of target algorithms that exceeded the memory limit: 0
{'accuracy': 0.861271676300578}
| | Preprocessing | Estimator | Weight |
|---:|:--------------------------------------------------------------|:----------------------------------------------------------------|---------:|
| 0 | SimpleImputer,NoEncoder,Normalizer,PowerTransformer | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.26 |
| 1 | None | KNNLearner | 0.14 |
| 2 | SimpleImputer,NoEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.12 |
| 3 | None | RFLearner | 0.1 |
| 4 | SimpleImputer,NoEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.1 |
| 5 | None | ETLearner | 0.08 |
| 6 | None | SVMLearner | 0.08 |
| 7 | SimpleImputer,NoEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.08 |
| 8 | None | LGBMLearner | 0.04 |
| 0 | SimpleImputer,NoEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.28 |
| 1 | None | RFLearner | 0.24 |
| 2 | None | KNNLearner | 0.16 |
| 3 | SimpleImputer,NoEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.12 |
| 4 | None | CBLearner | 0.08 |
| 5 | SimpleImputer,NoEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
| 6 | SimpleImputer,NoEncoder,StandardScaler,KernelPCA | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
| 7 | None | ETLearner | 0.02 |
| 8 | None | SVMLearner | 0.02 |
autoPyTorch results:
Dataset name: ad6f4912-4bc2-11ec-870e-7746ea156edb
Dataset name: ea262f4f-4bc4-11ec-8727-df8c3c818998
Optimisation Metric: accuracy
Best validation score: 0.8596491228070176
Number of target algorithm runs: 20
Number of successful target algorithm runs: 14
Best validation score: 0.8654970760233918
Number of target algorithm runs: 21
Number of successful target algorithm runs: 15
Number of crashed target algorithm runs: 5
Number of target algorithms that exceeded the time limit: 1
Number of target algorithms that exceeded the memory limit: 0
Expand Down Expand Up @@ -220,7 +218,7 @@ the search. Currently, there are two changes that can be made to the space:-
.. rst-class:: sphx-glr-timing

**Total running time of the script:** ( 5 minutes 59.297 seconds)
**Total running time of the script:** ( 5 minutes 45.859 seconds)


.. _sphx_glr_download_examples_40_advanced_example_custom_configuration_space.py:
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