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‎development/.buildinfo

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# Sphinx build info version 1
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# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
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config: da4a618284217d59a7915d1c6ebdf872
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config: 970eb458f32b434db48854a3317b2f05
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tags: 645f666f9bcd5a90fca523b33c5a78b7

‎development/_downloads/307f532dbef0476f85afc6b64b65f087/example_resampling_strategy.py

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############################################################################
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# Search for an ensemble of machine learning algorithms
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# -----------------------------------------------------------------------
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# -----------------------------------------------------
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api.search(
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X_train=X_train,
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############################################################################
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# Print the final ensemble performance
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# ------------
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# ------------------------------------
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y_pred = api.predict(X_test)
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score = api.score(y_pred, y_test)
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print(score)

‎development/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip

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‎development/_modules/autoPyTorch/api/tabular_classification.html

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<meta charset="utf-8" />
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<title>autoPyTorch.api.tabular_classification &#8212; AutoPyTorch 0.1.0 documentation</title>
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<title>autoPyTorch.api.tabular_classification &#8212; AutoPyTorch 0.1.1 documentation</title>
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‎development/_modules/autoPyTorch/api/tabular_regression.html

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<title>autoPyTorch.api.tabular_regression &#8212; AutoPyTorch 0.1.1 documentation</title>
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‎development/_modules/autoPyTorch/pipeline/tabular_classification.html

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‎development/_modules/autoPyTorch/pipeline/tabular_regression.html

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‎development/_modules/autoPyTorch/pipeline/traditional_tabular_classification.html

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‎development/_modules/autoPyTorch/pipeline/traditional_tabular_regression.html

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‎development/_sources/examples/20_basics/example_image_classification.rst.txt

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Pipeline Random Config:
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________________________________________
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Configuration:
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image_augmenter:GaussianBlur:sigma_min, Value: 2.1238678391388115
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image_augmenter:GaussianBlur:sigma_offset, Value: 2.7433341752045743
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image_augmenter:GaussianBlur:use_augmenter, Value: True
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image_augmenter:GaussianNoise:sigma_offset, Value: 0.7675514433357813
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image_augmenter:GaussianNoise:use_augmenter, Value: True
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image_augmenter:RandomAffine:use_augmenter, Value: False
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image_augmenter:GaussianBlur:use_augmenter, Value: False
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image_augmenter:GaussianNoise:use_augmenter, Value: False
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image_augmenter:RandomAffine:rotate, Value: 42
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image_augmenter:RandomAffine:scale_offset, Value: 0.26341164631974867
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image_augmenter:RandomAffine:shear, Value: 37
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image_augmenter:RandomAffine:translate_percent_offset, Value: 0.31257420399711705
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image_augmenter:RandomAffine:use_augmenter, Value: True
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**Total running time of the script:** ( 0 minutes 6.306 seconds)
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**Total running time of the script:** ( 0 minutes 6.470 seconds)
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.. _sphx_glr_download_examples_20_basics_example_image_classification.py:

‎development/_sources/examples/20_basics/example_tabular_classification.rst.txt

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| | Preprocessing | Estimator | Weight |
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| 0 | SimpleImputer,OneHotEncoder,Normalizer,KernelPCA | embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.2 |
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| 0 | SimpleImputer,OneHotEncoder,Normalizer,KernelPCA | embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.18 |
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| 2 | None | CBLearner | 0.14 |
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| 3 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.12 |
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| 4 | SimpleImputer,OneHotEncoder,Normalizer,PowerTransformer | embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.08 |
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| 5 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.08 |
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| 6 | SimpleImputer,OneHotEncoder,MinMaxScaler,PowerTransformer | embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
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| 7 | SimpleImputer,NoEncoder,Normalizer,Nystroem | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
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| 8 | None | SVMLearner | 0.04 |
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| 2 | None | SVMLearner | 0.12 |
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| 3 | None | CBLearner | 0.1 |
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| 4 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.08 |
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| 5 | SimpleImputer,OneHotEncoder,Normalizer,PowerTransformer | embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
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| 6 | None | RFLearner | 0.06 |
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| 7 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
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| 8 | SimpleImputer,OneHotEncoder,MinMaxScaler,PowerTransformer | embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
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| 9 | SimpleImputer,NoEncoder,Normalizer,Nystroem | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
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| 10 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
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| 11 | SimpleImputer,OneHotEncoder,Normalizer,TruncSVD | embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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| 12 | SimpleImputer,OneHotEncoder,MinMaxScaler,TruncSVD | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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| 13 | None | ETLearner | 0.02 |
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.. _sphx_glr_download_examples_20_basics_example_tabular_classification.py:

‎development/_sources/examples/20_basics/example_tabular_regression.rst.txt

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.. _sphx_glr_download_examples_20_basics_example_tabular_regression.py:

‎development/_sources/examples/20_basics/sg_execution_times.rst.txt

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=================
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**11:24.581** total execution time for **examples_20_basics** files:
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+--------------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_examples_20_basics_example_tabular_regression.py` (``example_tabular_regression.py``) | 05:49.238 | 0.0 MB |
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| :ref:`sphx_glr_examples_20_basics_example_tabular_regression.py` (``example_tabular_regression.py``) | 05:42.561 | 0.0 MB |
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+--------------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_examples_20_basics_example_tabular_classification.py` (``example_tabular_classification.py``) | 05:33.018 | 0.0 MB |
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| :ref:`sphx_glr_examples_20_basics_example_tabular_classification.py` (``example_tabular_classification.py``) | 05:35.550 | 0.0 MB |
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+--------------------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_examples_20_basics_example_image_classification.py` (``example_image_classification.py``) | 00:06.306 | 0.0 MB |
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| :ref:`sphx_glr_examples_20_basics_example_image_classification.py` (``example_image_classification.py``) | 00:06.470 | 0.0 MB |
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+--------------------------------------------------------------------------------------------------------------+-----------+--------+

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