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nabenabe0928: [refactor] Fix SparseMatrixType --> spmatrix and add ispandas (#397)
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‎development/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip

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‎development/_downloads/fb625db3c50d423b1b7881136ffdeec8/examples_jupyter.zip

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‎development/_images/sphx_glr_example_plot_over_time_001.png

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‎development/_images/sphx_glr_example_plot_over_time_thumb.png

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‎development/_images/sphx_glr_example_visualization_001.png

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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(values={
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'image_augmenter:GaussianBlur:sigma_min': 2.128854080819082,
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'image_augmenter:GaussianBlur:sigma_offset': 1.685286865327408,
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'image_augmenter:GaussianBlur:use_augmenter': True,
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'image_augmenter:GaussianNoise:use_augmenter': False,
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'image_augmenter:GaussianBlur:use_augmenter': False,
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'image_augmenter:GaussianNoise:sigma_offset': 2.016605350658349,
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'image_augmenter:GaussianNoise:use_augmenter': True,
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'image_augmenter:RandomAffine:use_augmenter': False,
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'image_augmenter:RandomCutout:p': 0.8505129226214392,
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'image_augmenter:RandomCutout:p': 0.7728298341875102,
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'image_augmenter:RandomCutout:use_augmenter': True,
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'image_augmenter:Resize:use_augmenter': False,
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'image_augmenter:ZeroPadAndCrop:percent': 0.3503163793523587,
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'normalizer:__choice__': 'NoNormalizer',
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'image_augmenter:ZeroPadAndCrop:percent': 0.4990785598329858,
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'normalizer:__choice__': 'ImageNormalizer',
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})
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Fitting the pipeline...
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________________________________________
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ImageClassificationPipeline
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________________________________________
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0-) normalizer:
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NoNormalizer
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ImageNormalizer
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1-) preprocessing:
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EarlyPreprocessing
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 0 minutes 6.887 seconds)
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**Total running time of the script:** ( 0 minutes 8.510 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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.. code-block:: none
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<autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f7e22bfd7f0>
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<autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f444a4d0d90>
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Optimisation Metric: accuracy
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Best validation score: 0.8713450292397661
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Number of target algorithm runs: 23
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Number of successful target algorithm runs: 21
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Number of successful target algorithm runs: 20
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Number of crashed target algorithm runs: 2
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Number of target algorithms that exceeded the time limit: 0
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Number of target algorithms that exceeded the time limit: 1
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Number of target algorithms that exceeded the memory limit: 0
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 5 minutes 31.215 seconds)
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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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.. code-block:: none
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<autoPyTorch.api.tabular_regression.TabularRegressionTask object at 0x7f7ebdf86d90>
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<autoPyTorch.api.tabular_regression.TabularRegressionTask object at 0x7f44e625f430>
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| 2 | SimpleImputer,Variance Threshold,NoCoalescer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.1 |
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| 3 | None | LGBMLearner | 0.04 |
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autoPyTorch results:
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Dataset name: 4d60e332-964c-11ec-87e7-95e9f01c72a4
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Dataset name: 6c9e9506-9a70-11ec-87d5-474e93987d34
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Optimisation Metric: r2
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Best validation score: 0.8670098636440993
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Number of target algorithm runs: 27
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Number of successful target algorithm runs: 25
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Number of crashed target algorithm runs: 1
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Number of target algorithm runs: 24
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Number of successful target algorithm runs: 23
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Number of crashed target algorithm runs: 0
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Number of target algorithms that exceeded the time limit: 1
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Number of target algorithms that exceeded the memory limit: 0
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 5 minutes 34.491 seconds)
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**Total running time of the script:** ( 5 minutes 33.512 seconds)
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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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Computation times
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=================
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**11:10.330** total execution time for **examples_20_basics** files:
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**11:13.237** 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``) | 05:34.491 | 0.0 MB |
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| :ref:`sphx_glr_examples_20_basics_example_tabular_regression.py` (``example_tabular_regression.py``) | 05:33.512 | 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``) | 05:28.953 | 0.0 MB |
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| :ref:`sphx_glr_examples_20_basics_example_tabular_classification.py` (``example_tabular_classification.py``) | 05:31.215 | 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``) | 00:06.887 | 0.0 MB |
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| :ref:`sphx_glr_examples_20_basics_example_image_classification.py` (``example_image_classification.py``) | 00:08.510 | 0.0 MB |
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+--------------------------------------------------------------------------------------------------------------+-----------+--------+

‎development/_sources/examples/40_advanced/example_custom_configuration_space.rst.txt

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.. code-block:: none
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<autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f7e22069580>
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<autoPyTorch.api.tabular_classification.TabularClassificationTask object at 0x7f4449514820>
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.. code-block:: none
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{'accuracy': 0.8497109826589595}
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{'accuracy': 0.838150289017341}
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| | Preprocessing | Estimator | Weight |
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|---:|:-------------------------------------------------------------------------------------------------|:-------------------------------------------------------------|---------:|
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| 0 | SimpleImputer,Variance Threshold,NoCoalescer,OneHotEncoder,MinMaxScaler,PolynomialFeatures | embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.56 |
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| 1 | SimpleImputer,Variance Threshold,MinorityCoalescer,OneHotEncoder,RobustScaler,KitchenSink | embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.16 |
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| 2 | None | RFLearner | 0.08 |
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| 3 | SimpleImputer,Variance Threshold,MinorityCoalescer,OneHotEncoder,PowerTransformer,Nystroem | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
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| 4 | SimpleImputer,Variance Threshold,NoCoalescer,OneHotEncoder,MinMaxScaler,TruncSVD | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
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| 5 | None | ETLearner | 0.04 |
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| 6 | SimpleImputer,Variance Threshold,NoCoalescer,OneHotEncoder,QuantileTransformer,KitchenSink | embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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| 7 | None | LGBMLearner | 0.02 |
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| 8 | SimpleImputer,Variance Threshold,NoCoalescer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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| 0 | SimpleImputer,Variance Threshold,NoCoalescer,OneHotEncoder,MinMaxScaler,PolynomialFeatures | embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.2 |
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| 1 | SimpleImputer,Variance Threshold,MinorityCoalescer,OneHotEncoder,PowerTransformer,Nystroem | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.16 |
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| 2 | SimpleImputer,Variance Threshold,MinorityCoalescer,OneHotEncoder,RobustScaler,KitchenSink | embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.12 |
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| 3 | SimpleImputer,Variance Threshold,NoCoalescer,OneHotEncoder,MinMaxScaler,TruncSVD | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.1 |
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| 4 | None | RFLearner | 0.1 |
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| 5 | None | SVMLearner | 0.1 |
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| 6 | None | ETLearner | 0.06 |
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| 7 | None | LGBMLearner | 0.04 |
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| 8 | None | KNNLearner | 0.04 |
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| 9 | SimpleImputer,Variance Threshold,NoCoalescer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
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| 10 | SimpleImputer,Variance Threshold,MinorityCoalescer,OneHotEncoder,NoScaler,PolynomialFeatures | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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| 11 | SimpleImputer,Variance Threshold,NoCoalescer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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Dataset name: ebc28c6f-9a73-11ec-87d5-474e93987d34
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Number of target algorithm runs: 18
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| 7 | SimpleImputer,Variance Threshold,NoCoalescer,NoEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
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| 8 | SimpleImputer,Variance Threshold,NoCoalescer,NoEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
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autoPyTorch results:
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Dataset name: 533c0306-9a74-11ec-87d5-474e93987d34
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**Total running time of the script:** ( 5 minutes 46.242 seconds)
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.. _sphx_glr_download_examples_40_advanced_example_custom_configuration_space.py:

‎development/_sources/examples/40_advanced/example_parallel_n_jobs.rst.txt

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Dataset name: 0be6cebd-9a73-11ec-87d5-474e93987d34
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Number of crashed target algorithm runs: 6
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.. _sphx_glr_download_examples_40_advanced_example_parallel_n_jobs.py:

‎development/_sources/examples/40_advanced/example_plot_over_time.rst.txt

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.. _sphx_glr_download_examples_40_advanced_example_plot_over_time.py:

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