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ArlindKadra: Updating implementation of the reg cocktails so that it is compatible with fixed search space updates
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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 0x7f02e2e973d0> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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<smac.runhistory.runhistory.RunHistory object at 0x7efeb6ade400> [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=0.002084016799926758, budget=0), TrajEntry(train_perf=0.14035087719298245, incumbent_id=1, incumbent=Configuration:
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.001983165740966797, budget=0), TrajEntry(train_perf=0.15204678362573099, 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'
@@ -128,21 +128,57 @@ 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=5.20469331741333, wallclock_time=6.656493186950684, 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 | None | CatBoostClassifier | 0.2 |
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| 1 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.16 |
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| 2 | None | ExtraTreesClassifier | 0.14 |
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| 3 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.14 |
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| 4 | SimpleImputer,OneHotEncoder,NoScaler,PolynomialFeatures | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.12 |
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| 5 | None | LGBMClassifier | 0.08 |
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| 6 | None | RFClassifier | 0.06 |
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| 7 | None | KNNClassifier | 0.06 |
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| 8 | None | SVC | 0.02 |
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| 9 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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<smac.runhistory.runhistory.RunHistory object at 0x7f02e0a1c6a0> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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, ta_runs=1, ta_time_used=5.583842515945435, wallclock_time=7.051768779754639, budget=5.555555555555555), TrajEntry(train_perf=0.1871345029239766, incumbent_id=2, incumbent=Configuration:
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data_loader:batch_size, Value: 409
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encoder:__choice__, Value: 'OneHotEncoder'
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feature_preprocessor:TruncatedSVD:target_dim, Value: 4
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feature_preprocessor:__choice__, Value: 'TruncatedSVD'
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imputer:categorical_strategy, Value: 'most_frequent'
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imputer:numerical_strategy, Value: 'constant_zero'
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lr_scheduler:CosineAnnealingLR:T_max, Value: 53
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lr_scheduler:__choice__, Value: 'CosineAnnealingLR'
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network_backbone:MLPBackbone:activation, Value: 'relu'
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network_backbone:MLPBackbone:dropout_1, Value: 0.7173131362280667
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network_backbone:MLPBackbone:dropout_2, Value: 0.32527643996037753
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network_backbone:MLPBackbone:num_groups, Value: 2
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network_backbone:MLPBackbone:num_units_1, Value: 165
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network_backbone:MLPBackbone:num_units_2, Value: 244
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network_backbone:MLPBackbone:use_dropout, Value: True
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network_backbone:__choice__, Value: 'MLPBackbone'
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network_embedding:__choice__, Value: 'NoEmbedding'
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network_head:__choice__, Value: 'fully_connected'
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network_head:fully_connected:activation, Value: 'tanh'
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network_head:fully_connected:num_layers, Value: 3
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network_head:fully_connected:units_layer_1, Value: 256
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network_head:fully_connected:units_layer_2, Value: 408
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network_init:OrthogonalInit:bias_strategy, Value: 'Normal'
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network_init:__choice__, Value: 'OrthogonalInit'
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optimizer:RMSpropOptimizer:alpha, Value: 0.44965916725624266
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optimizer:RMSpropOptimizer:lr, Value: 0.0015378712542410064
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optimizer:RMSpropOptimizer:momentum, Value: 0.7354696550868378
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optimizer:RMSpropOptimizer:use_weight_decay, Value: True
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optimizer:RMSpropOptimizer:weight_decay, Value: 3.025630486858573e-06
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optimizer:__choice__, Value: 'RMSpropOptimizer'
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scaler:__choice__, Value: 'StandardScaler'
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trainer:RowCutOutTrainer:cutout_prob, Value: 0.589936979878005
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trainer:RowCutOutTrainer:patch_ratio, Value: 0.40724571391547737
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trainer:RowCutOutTrainer:use_lookahead_optimizer, Value: False
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trainer:RowCutOutTrainer:use_snapshot_ensemble, Value: False
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trainer:RowCutOutTrainer:use_stochastic_weight_averaging, Value: True
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trainer:RowCutOutTrainer:weighted_loss, Value: True
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trainer:__choice__, Value: 'RowCutOutTrainer'
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, ta_runs=13, ta_time_used=87.67640423774719, wallclock_time=120.08723640441895, budget=50.0)]
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{'accuracy': 0.861271676300578}
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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 | 0.24 |
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| 2 | SimpleImputer,OneHotEncoder,NoScaler,PolynomialFeatures | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.2 |
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| 3 | None | CatBoostClassifier | 0.18 |
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| 4 | None | KNNClassifier | 0.06 |
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| 5 | SimpleImputer,OneHotEncoder,StandardScaler,TruncSVD | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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| 6 | SimpleImputer,OneHotEncoder,StandardScaler,TruncSVD | no embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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<smac.runhistory.runhistory.RunHistory object at 0x7efeb7182220> [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'
@@ -181,7 +217,7 @@ 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=0.0016298294067382812, budget=0), TrajEntry(train_perf=0.20467836257309946, incumbent_id=1, incumbent=Configuration:
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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.0017466545104980469, 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'
@@ -220,59 +256,17 @@ 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, Value: True
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trainer:__choice__, Value: 'StandardTrainer'
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, ta_runs=1, ta_time_used=4.402615785598755, wallclock_time=5.924044609069824, budget=5.555555555555555), TrajEntry(train_perf=0.18128654970760238, incumbent_id=2, incumbent=Configuration:
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data_loader:batch_size, Value: 215
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encoder:__choice__, Value: 'NoEncoder'
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feature_preprocessor:__choice__, Value: 'NoFeaturePreprocessor'
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imputer:categorical_strategy, Value: 'constant_!missing!'
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imputer:numerical_strategy, Value: 'most_frequent'
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lr_scheduler:CosineAnnealingLR:T_max, Value: 51
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lr_scheduler:__choice__, Value: 'CosineAnnealingLR'
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network_backbone:ShapedResNetBackbone:activation, Value: 'tanh'
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network_backbone:ShapedResNetBackbone:blocks_per_group, Value: 2
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network_backbone:ShapedResNetBackbone:max_dropout, Value: 0.37376142861116285
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network_backbone:ShapedResNetBackbone:max_units, Value: 106
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network_backbone:ShapedResNetBackbone:multi_branch_choice, Value: 'None'
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network_backbone:ShapedResNetBackbone:num_groups, Value: 1
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network_backbone:ShapedResNetBackbone:output_dim, Value: 979
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network_backbone:ShapedResNetBackbone:resnet_shape, Value: 'stairs'
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network_backbone:ShapedResNetBackbone:use_batch_norm, Value: False
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network_backbone:ShapedResNetBackbone:use_dropout, Value: True
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network_backbone:ShapedResNetBackbone:use_skip_connection, Value: True
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network_backbone:__choice__, Value: 'ShapedResNetBackbone'
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network_embedding:__choice__, Value: 'NoEmbedding'
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network_head:__choice__, Value: 'fully_connected'
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network_head:fully_connected:num_layers, Value: 1
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network_init:XavierInit:bias_strategy, Value: 'Normal'
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network_init:__choice__, Value: 'XavierInit'
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optimizer:RMSpropOptimizer:alpha, Value: 0.21475647146537818
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optimizer:RMSpropOptimizer:lr, Value: 0.06800579072253359
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optimizer:RMSpropOptimizer:momentum, Value: 0.19455509625221876
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optimizer:RMSpropOptimizer:use_weight_decay, Value: False
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optimizer:__choice__, Value: 'RMSpropOptimizer'
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scaler:Normalizer:norm, Value: 'max'
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scaler:__choice__, Value: 'Normalizer'
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trainer:RowCutMixTrainer:Lookahead:la_alpha, Value: 0.6084931276595258
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trainer:RowCutMixTrainer:Lookahead:la_steps, Value: 8
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trainer:RowCutMixTrainer:alpha, Value: 0.6686915138304311
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trainer:RowCutMixTrainer:se_lastk, Constant: 3
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trainer:RowCutMixTrainer:use_lookahead_optimizer, Value: True
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trainer:RowCutMixTrainer:use_snapshot_ensemble, Value: True
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trainer:RowCutMixTrainer:use_stochastic_weight_averaging, Value: True
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trainer:RowCutMixTrainer:weighted_loss, Value: False
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trainer:__choice__, Value: 'RowCutMixTrainer'
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, ta_runs=18, ta_time_used=125.97386693954468, wallclock_time=184.2776644229889, budget=50.0)]
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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 | 0.22 |
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| 1 | None | CatBoostClassifier | 0.2 |
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| 2 | None | RFClassifier | 0.2 |
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| 3 | SimpleImputer,NoEncoder,NoScaler,NoFeaturePreprocessing | no embedding,ShapedResNetBackbone,FullyConnectedHead,nn.Sequential | 0.18 |
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| 4 | None | KNNClassifier | 0.08 |
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| 5 | SimpleImputer,NoEncoder,Normalizer,Nystroem | no embedding,ShapedResNetBackbone,FullyConnectedHead,nn.Sequential | 0.06 |
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| 6 | SimpleImputer,NoEncoder,Normalizer,NoFeaturePreprocessing | no embedding,ShapedResNetBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
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| 7 | None | LGBMClassifier | 0.02 |
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, ta_runs=1, ta_time_used=4.803942680358887, wallclock_time=6.263315200805664, 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 | 0.38 |
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| 1 | None | ExtraTreesClassifier | 0.22 |
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| 2 | None | CatBoostClassifier | 0.2 |
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| 3 | None | KNNClassifier | 0.1 |
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| 4 | SimpleImputer,NoEncoder,Normalizer,NoFeaturePreprocessing | no embedding,ShapedResNetBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
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| 5 | None | SVC | 0.04 |
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| 6 | SimpleImputer,NoEncoder,StandardScaler,NoFeaturePreprocessing | no embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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@@ -401,7 +395,7 @@ 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 41.996 seconds)
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**Total running time of the script:** ( 11 minutes 51.552 seconds)
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.. _sphx_glr_download_advanced_tabular_example_custom_configuration_space.py:

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