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Arlind Kadra: Cocktail hotfixes (#245)
1 parent f7c29d1 commit fdbdaf1

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‎refactor_development_regularization_cocktails/_downloads/2f0f54a9831653ac5c12ee0e06324a62/basics_tabular_jupyter.zip

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‎refactor_development_regularization_cocktails/_downloads/8ef6602cf8ed40221edd89244fb031af/basics_tabular_python.zip

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‎refactor_development_regularization_cocktails/_downloads/b38295cf56f02b1c4547385a8f389f90/advanced_tabular_python.zip

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‎refactor_development_regularization_cocktails/_downloads/df038041811db9bd567de83692a8f994/advanced_tabular_jupyter.zip

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‎refactor_development_regularization_cocktails/_sources/advanced_tabular/example_custom_configuration_space.rst.txt

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@@ -46,7 +46,7 @@ the search. Currently, there are two changes that can be made to the space:-
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.. code-block:: none
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<smac.runhistory.runhistory.RunHistory object at 0x7f93a5e510a0> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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<smac.runhistory.runhistory.RunHistory object at 0x7f23aef65a00> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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data_loader:batch_size, Value: 32
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encoder:__choice__, Value: 'OneHotEncoder'
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feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
@@ -87,7 +87,7 @@ the search. Currently, there are two changes that can be made to the space:-
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trainer:StandardTrainer:use_stochastic_weight_averaging, Value: True
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trainer:StandardTrainer:weighted_loss, Value: True
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.001966238021850586, budget=0), TrajEntry(train_perf=0.16959064327485385, incumbent_id=1, incumbent=Configuration:
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.00153350830078125, budget=0), TrajEntry(train_perf=0.16959064327485385, incumbent_id=1, incumbent=Configuration:
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data_loader:batch_size, Value: 32
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encoder:__choice__, Value: 'OneHotEncoder'
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feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
@@ -128,7 +128,7 @@ the search. Currently, there are two changes that can be made to the space:-
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trainer:StandardTrainer:use_stochastic_weight_averaging, Value: True
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trainer:StandardTrainer:weighted_loss, Value: True
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=1, ta_time_used=11.944680213928223, wallclock_time=13.435033559799194, budget=5.555555555555555), TrajEntry(train_perf=0.1578947368421053, incumbent_id=2, incumbent=Configuration:
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, ta_runs=1, ta_time_used=15.69832968711853, wallclock_time=17.184927701950073, budget=5.555555555555555), TrajEntry(train_perf=0.1578947368421053, incumbent_id=2, incumbent=Configuration:
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data_loader:batch_size, Value: 109
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encoder:__choice__, Value: 'OneHotEncoder'
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feature_preprocessor:RandomKitchenSinks:gamma, Value: 0.08890013438983504
@@ -170,15 +170,16 @@ the search. Currently, there are two changes that can be made to the space:-
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trainer:RowCutMixTrainer:use_stochastic_weight_averaging, Value: False
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trainer:RowCutMixTrainer:weighted_loss, Value: True
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trainer:__choice__, Value: 'RowCutMixTrainer'
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, ta_runs=9, ta_time_used=132.09137415885925, wallclock_time=152.75405263900757, budget=5.555555555555555)]
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{'accuracy': 0.8670520231213873}
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| | Preprocessing | Estimator | Weight |
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|---:|:----------------------------------------------|:-------------------------------------------|---------:|
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| 0 | SimpleImputer,OneHotEncoder,NoScaler,Nystroem | embedding,MLPBackbone,NoHead,nn.Sequential | 0.5 |
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| 1 | SimpleImputer,OneHotEncoder,NoScaler,Nystroem | embedding,MLPBackbone,NoHead,nn.Sequential | 0.44 |
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| 2 | None | ExtraTreesClassifier | 0.04 |
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| 3 | None | LGBMClassifier | 0.02 |
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<smac.runhistory.runhistory.RunHistory object at 0x7f93a52f0df0> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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, ta_runs=9, ta_time_used=170.7749261856079, wallclock_time=192.11866116523743, budget=5.555555555555555)]
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{'accuracy': 0.8786127167630058}
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| | Preprocessing | Estimator | Weight |
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|---:|:------------------------------------------------------------------|:----------------------------------------------------------|---------:|
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| 0 | SimpleImputer,OneHotEncoder,NoScaler,Nystroem | embedding,MLPBackbone,NoHead,nn.Sequential | 0.9 |
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| 1 | None | RFClassifier | 0.04 |
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| 2 | None | LGBMClassifier | 0.02 |
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| 3 | None | SVC | 0.02 |
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| 4 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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<smac.runhistory.runhistory.RunHistory object at 0x7f23adec0af0> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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data_loader:batch_size, Value: 32
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encoder:__choice__, Value: 'NoEncoder'
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feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
@@ -217,7 +218,7 @@ the search. Currently, there are two changes that can be made to the space:-
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trainer:StandardTrainer:use_stochastic_weight_averaging, Value: True
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trainer:StandardTrainer:weighted_loss, Value: True
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0016541481018066406, budget=0), TrajEntry(train_perf=0.1871345029239766, incumbent_id=1, incumbent=Configuration:
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0011212825775146484, budget=0), TrajEntry(train_perf=0.19298245614035092, incumbent_id=1, incumbent=Configuration:
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data_loader:batch_size, Value: 32
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encoder:__choice__, Value: 'NoEncoder'
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feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
@@ -256,16 +257,15 @@ the search. Currently, there are two changes that can be made to the space:-
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trainer:StandardTrainer:use_stochastic_weight_averaging, Value: True
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trainer:StandardTrainer:weighted_loss, Value: True
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=1, ta_time_used=8.343164443969727, wallclock_time=9.81375765800476, budget=5.555555555555555)]
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{'accuracy': 0.8670520231213873}
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| | Preprocessing | Estimator | Weight |
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|---:|:--------------------------------------------------------------|:----------------------------------------------------------------|---------:|
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| 0 | None | RFClassifier | 0.36 |
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| 1 | None | LGBMClassifier | 0.28 |
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| 2 | None | ExtraTreesClassifier | 0.18 |
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| 3 | None | KNNClassifier | 0.1 |
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| 4 | None | CatBoostClassifier | 0.06 |
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| 5 | SimpleImputer,NoEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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, ta_runs=1, ta_time_used=10.127033948898315, wallclock_time=11.634387731552124, budget=5.555555555555555)]
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{'accuracy': 0.8728323699421965}
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| | Preprocessing | Estimator | Weight |
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|---:|:----------------|:---------------------|---------:|
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| 0 | None | ExtraTreesClassifier | 0.38 |
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| 1 | None | LGBMClassifier | 0.2 |
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| 2 | None | RFClassifier | 0.2 |
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| 3 | None | KNNClassifier | 0.14 |
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| 4 | None | CatBoostClassifier | 0.08 |
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@@ -394,7 +394,7 @@ the search. Currently, there are two changes that can be made to the space:-
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 11 minutes 36.099 seconds)
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**Total running time of the script:** ( 11 minutes 40.629 seconds)
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.. _sphx_glr_download_advanced_tabular_example_custom_configuration_space.py:

‎refactor_development_regularization_cocktails/_sources/advanced_tabular/example_resampling_strategy.rst.txt

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@@ -38,7 +38,7 @@ a 67% train size split.
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.. code-block:: none
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<smac.runhistory.runhistory.RunHistory object at 0x7f93a5e55c40> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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<smac.runhistory.runhistory.RunHistory object at 0x7f23ad174160> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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data_loader:batch_size, Value: 64
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encoder:__choice__, Value: 'OneHotEncoder'
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feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
@@ -77,7 +77,7 @@ a 67% train size split.
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trainer:StandardTrainer:use_stochastic_weight_averaging, Value: True
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trainer:StandardTrainer:weighted_loss, Value: True
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.002051115036010742, budget=0), TrajEntry(train_perf=0.19298245614035092, incumbent_id=1, incumbent=Configuration:
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0018305778503417969, budget=0), TrajEntry(train_perf=0.19298245614035092, incumbent_id=1, incumbent=Configuration:
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data_loader:batch_size, Value: 64
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encoder:__choice__, Value: 'OneHotEncoder'
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feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
@@ -116,18 +116,19 @@ a 67% train size split.
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trainer:StandardTrainer:use_stochastic_weight_averaging, Value: True
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trainer:StandardTrainer:weighted_loss, Value: True
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=1, ta_time_used=12.115590572357178, wallclock_time=13.64609694480896, budget=5.555555555555555)]
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{'accuracy': 0.8728323699421965}
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, ta_runs=1, ta_time_used=15.317967414855957, wallclock_time=16.835456609725952, budget=5.555555555555555)]
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{'accuracy': 0.8670520231213873}
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| | Preprocessing | Estimator | Weight |
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|---:|:------------------------------------------------------------------|:----------------------------------------------------------------|---------:|
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| 0 | None | RFClassifier | 0.28 |
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| 1 | None | ExtraTreesClassifier | 0.2 |
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| 2 | None | CatBoostClassifier | 0.18 |
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| 0 | None | CatBoostClassifier | 0.22 |
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| 1 | None | RFClassifier | 0.22 |
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| 2 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.18 |
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| 3 | None | LGBMClassifier | 0.16 |
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| 4 | None | KNNClassifier | 0.12 |
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| 5 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
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| 6 | SimpleImputer,OneHotEncoder,Normalizer,KitchenSink | no embedding,ShapedResNetBackbone,NoHead,nn.Sequential | 0.02 |
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<smac.runhistory.runhistory.RunHistory object at 0x7f93a5d58070> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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| 4 | None | ExtraTreesClassifier | 0.12 |
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| 5 | SimpleImputer,OneHotEncoder,Normalizer,KitchenSink | no embedding,ShapedResNetBackbone,NoHead,nn.Sequential | 0.04 |
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| 6 | None | SVC | 0.04 |
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| 7 | None | KNNClassifier | 0.02 |
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<smac.runhistory.runhistory.RunHistory object at 0x7f23ac354130> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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data_loader:batch_size, Value: 64
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encoder:__choice__, Value: 'OneHotEncoder'
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feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
@@ -166,7 +167,7 @@ a 67% train size split.
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trainer:StandardTrainer:use_stochastic_weight_averaging, Value: True
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trainer:StandardTrainer:weighted_loss, Value: True
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0020253658294677734, budget=0), TrajEntry(train_perf=0.13918253373732403, incumbent_id=1, incumbent=Configuration:
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.001428365707397461, budget=0), TrajEntry(train_perf=1.0, incumbent_id=1, incumbent=Configuration:
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data_loader:batch_size, Value: 64
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encoder:__choice__, Value: 'OneHotEncoder'
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feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
@@ -205,18 +206,17 @@ a 67% train size split.
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trainer:StandardTrainer:use_stochastic_weight_averaging, Value: True
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trainer:StandardTrainer:weighted_loss, Value: True
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=1, ta_time_used=31.310828924179077, wallclock_time=32.82950496673584, budget=5.555555555555555)]
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, ta_runs=1, ta_time_used=32.74102234840393, wallclock_time=34.25397086143494, budget=5.555555555555555)]
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{'accuracy': 0.8728323699421965}
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| | Preprocessing | Estimator | Weight |
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|---:|:------------------------------------------------------------------|:----------------------------------------------------------------|---------:|
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| 0 | None | TabularClassifier | 0.28 |
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| 1 | None | TabularClassifier | 0.18 |
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| 2 | None | TabularClassifier | 0.16 |
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| 3 | None | TabularClassifier | 0.12 |
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| 4 | None | TabularClassifier | 0.12 |
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| 5 | None | TabularClassifier | 0.08 |
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| 6 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
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<smac.runhistory.runhistory.RunHistory object at 0x7f93a46b2700> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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| | Preprocessing | Estimator | Weight |
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|---:|:----------------|:------------------|---------:|
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| 0 | None | TabularClassifier | 0.24 |
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| 1 | None | TabularClassifier | 0.24 |
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| 2 | None | TabularClassifier | 0.18 |
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| 3 | None | TabularClassifier | 0.16 |
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| 4 | None | TabularClassifier | 0.12 |
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| 5 | None | TabularClassifier | 0.06 |
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<smac.runhistory.runhistory.RunHistory object at 0x7f23ad1d7370> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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data_loader:batch_size, Value: 64
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@@ -255,7 +255,7 @@ a 67% train size split.
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trainer:StandardTrainer:use_stochastic_weight_averaging, Value: True
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trainer:StandardTrainer:weighted_loss, Value: True
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0019996166229248047, budget=0), TrajEntry(train_perf=0.16959064327485385, incumbent_id=1, incumbent=Configuration:
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0017085075378417969, budget=0), TrajEntry(train_perf=0.16959064327485385, incumbent_id=1, incumbent=Configuration:
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encoder:__choice__, Value: 'OneHotEncoder'
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feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
@@ -294,15 +294,15 @@ a 67% train size split.
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trainer:StandardTrainer:use_stochastic_weight_averaging, Value: True
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trainer:StandardTrainer:weighted_loss, Value: True
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=1, ta_time_used=12.241821527481079, wallclock_time=13.771500825881958, budget=5.555555555555555)]
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, ta_runs=1, ta_time_used=15.288289785385132, wallclock_time=16.83263635635376, budget=5.555555555555555)]
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{'accuracy': 0.884393063583815}
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| | Preprocessing | Estimator | Weight |
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|---:|:---------------------------------------------------|:-------------------------------------------------------|---------:|
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| 0 | None | CatBoostClassifier | 0.66 |
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| 0 | None | CatBoostClassifier | 0.64 |
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| 1 | None | ExtraTreesClassifier | 0.14 |
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| 2 | None | LGBMClassifier | 0.08 |
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| 3 | None | RFClassifier | 0.08 |
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| 4 | SimpleImputer,OneHotEncoder,Normalizer,KitchenSink | no embedding,ShapedResNetBackbone,NoHead,nn.Sequential | 0.02 |
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| 2 | None | RFClassifier | 0.1 |
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| 3 | None | LGBMClassifier | 0.06 |
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| 4 | SimpleImputer,OneHotEncoder,Normalizer,KitchenSink | no embedding,ShapedResNetBackbone,NoHead,nn.Sequential | 0.04 |
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| 5 | None | SVC | 0.02 |
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 10 minutes 2.984 seconds)
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**Total running time of the script:** ( 10 minutes 14.183 seconds)
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.. _sphx_glr_download_advanced_tabular_example_resampling_strategy.py:

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