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Ravin Kohli: Reproducibility in cocktail (#204)
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refactor_development_regularization_cocktails/_sources/advanced_tabular/example_custom_configuration_space.rst.txt

Lines changed: 27 additions & 25 deletions
Original file line numberDiff line numberDiff line change
@@ -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 0x7f35a7c0b940> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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<smac.runhistory.runhistory.RunHistory object at 0x7f69d7b96f10> [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, Constant: 1
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.00197601318359375, 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=0.0021958351135253906, 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'
@@ -128,16 +128,19 @@ 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, Constant: 1
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=1, ta_time_used=12.787853240966797, wallclock_time=14.251850366592407, 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 | 0.4 |
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| 1 | None | RFClassifier | 0.24 |
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| 2 | None | LGBMClassifier | 0.2 |
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| 3 | None | KNNClassifier | 0.12 |
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| 4 | None | CatBoostClassifier | 0.04 |
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<smac.runhistory.runhistory.RunHistory object at 0x7f35a7c0bfa0> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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, ta_runs=1, ta_time_used=15.160608291625977, wallclock_time=16.63932466506958, 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 | CatBoostClassifier | 0.34 |
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| 1 | None | RFClassifier | 0.24 |
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| 2 | SimpleImputer,OneHotEncoder,NoScaler,PolynomialFeatures | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.14 |
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| 3 | None | ExtraTreesClassifier | 0.1 |
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| 4 | None | LGBMClassifier | 0.08 |
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| 5 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
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| 6 | None | SVC | 0.02 |
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| 7 | None | KNNClassifier | 0.02 |
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<smac.runhistory.runhistory.RunHistory object at 0x7f69ed87a580> [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'
@@ -176,7 +179,7 @@ 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, Constant: 1
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.001708984375, budget=0), TrajEntry(train_perf=0.2222222222222222, incumbent_id=1, incumbent=Configuration:
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0015273094177246094, budget=0), TrajEntry(train_perf=0.2222222222222222, 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'
@@ -215,18 +218,17 @@ 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, Constant: 1
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=1, ta_time_used=8.091186046600342, wallclock_time=9.551165580749512, budget=5.555555555555555)]
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, ta_runs=1, ta_time_used=9.499428987503052, wallclock_time=10.939727783203125, budget=5.555555555555555)]
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{'accuracy': 0.8554913294797688}
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| | Preprocessing | Estimator | Weight |
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|---:|:----------------------------------------------------|:----------------------------------------------------------------|---------:|
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| 0 | SimpleImputer,NoEncoder,NoScaler,PolynomialFeatures | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.4 |
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| 1 | None | CatBoostClassifier | 0.16 |
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| 2 | SimpleImputer,NoEncoder,Normalizer,KernelPCA | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.14 |
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| 3 | None | LGBMClassifier | 0.1 |
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| 4 | None | ExtraTreesClassifier | 0.08 |
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| 5 | None | RFClassifier | 0.06 |
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| 6 | None | SVC | 0.04 |
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| 7 | SimpleImputer,NoEncoder,NoScaler,PolynomialFeatures | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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| | Preprocessing | Estimator | Weight |
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|---:|:----------------------------------------------------|:-------------------------------------------------------------|---------:|
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| 0 | SimpleImputer,NoEncoder,NoScaler,PolynomialFeatures | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.7 |
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| 1 | None | RFClassifier | 0.1 |
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| 2 | None | CatBoostClassifier | 0.06 |
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| 3 | SimpleImputer,NoEncoder,NoScaler,PolynomialFeatures | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
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| 4 | None | LGBMClassifier | 0.04 |
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| 5 | None | ExtraTreesClassifier | 0.04 |
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| 6 | None | SVC | 0.02 |
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@@ -355,7 +357,7 @@ 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 40.879 seconds)
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**Total running time of the script:** ( 11 minutes 37.611 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

Lines changed: 27 additions & 29 deletions
Original file line numberDiff line numberDiff line change
@@ -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 0x7f35a79806a0> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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<smac.runhistory.runhistory.RunHistory object at 0x7f69eda5e670> [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, Constant: 1
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0018994808197021484, 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=0.0019121170043945312, budget=0), TrajEntry(train_perf=0.16959064327485385, 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'
@@ -116,19 +116,18 @@ 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, Constant: 1
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=1, ta_time_used=12.164043426513672, wallclock_time=13.653866529464722, budget=5.555555555555555)]
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{'accuracy': 0.8786127167630058}
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, ta_runs=1, ta_time_used=14.97559404373169, wallclock_time=16.456933736801147, 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 | SimpleImputer,OneHotEncoder,Normalizer,PolynomialFeatures | embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.18 |
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| 1 | None | LGBMClassifier | 0.18 |
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| 2 | None | RFClassifier | 0.18 |
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| 3 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.16 |
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| 4 | None | CatBoostClassifier | 0.14 |
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| 5 | None | ExtraTreesClassifier | 0.1 |
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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 0x7f35c2192be0> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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| 0 | None | LGBMClassifier | 0.22 |
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| 1 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.22 |
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| 2 | None | ExtraTreesClassifier | 0.2 |
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| 3 | None | RFClassifier | 0.16 |
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| 4 | None | SVC | 0.1 |
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| 5 | None | CatBoostClassifier | 0.08 |
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| 6 | None | KNNClassifier | 0.02 |
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<smac.runhistory.runhistory.RunHistory object at 0x7f69d7e87f10> [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'
@@ -167,7 +166,7 @@ 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, Constant: 1
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0021066665649414062, budget=0), TrajEntry(train_perf=0.1623768221379145, incumbent_id=1, incumbent=Configuration:
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0020830631256103516, budget=0), TrajEntry(train_perf=1.0, incumbent_id=1, incumbent=Configuration:
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encoder:__choice__, Value: 'OneHotEncoder'
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feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
@@ -206,18 +205,17 @@ 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, Constant: 1
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=1, ta_time_used=30.45268940925598, wallclock_time=31.921412467956543, budget=5.555555555555555)]
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{'accuracy': 0.8554913294797688}
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| | Preprocessing | Estimator | Weight |
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|---:|:------------------------------------------------------------------|:----------------------------------------------------------------|---------:|
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| 0 | None | TabularClassifier | 0.22 |
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| 1 | None | TabularClassifier | 0.22 |
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| 2 | None | TabularClassifier | 0.22 |
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| 3 | None | TabularClassifier | 0.16 |
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| 4 | None | TabularClassifier | 0.1 |
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| 5 | None | TabularClassifier | 0.06 |
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| 6 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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<smac.runhistory.runhistory.RunHistory object at 0x7f35a75718e0> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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, ta_runs=1, ta_time_used=32.47600293159485, wallclock_time=33.94159984588623, 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 | 0.24 |
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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 0x7f69edc521f0> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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@@ -256,7 +254,7 @@ 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, Constant: 1
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0021975040435791016, budget=0), TrajEntry(train_perf=0.16374269005847952, incumbent_id=1, incumbent=Configuration:
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0020017623901367188, budget=0), TrajEntry(train_perf=0.16374269005847952, incumbent_id=1, incumbent=Configuration:
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data_loader:batch_size, Value: 64
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@@ -295,7 +293,7 @@ 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, Constant: 1
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=1, ta_time_used=12.529094219207764, wallclock_time=14.05341625213623, budget=5.555555555555555)]
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, ta_runs=1, ta_time_used=15.390185832977295, wallclock_time=16.844798803329468, budget=5.555555555555555)]
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{'accuracy': 0.884393063583815}
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| | Preprocessing | Estimator | Weight |
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|---:|:----------------|:---------------------|---------:|
@@ -466,7 +464,7 @@ a 67% train size split.
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 9 minutes 58.270 seconds)
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**Total running time of the script:** ( 10 minutes 7.307 seconds)
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.. _sphx_glr_download_advanced_tabular_example_resampling_strategy.py:

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