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Arlind Kadra: Updating search space (#156)
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‎refactor_development_regularization_cocktails/_downloads/bc82bea3a5dd7bdba60b65220891d9e5/examples_python.zip

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‎refactor_development_regularization_cocktails/_downloads/fb625db3c50d423b1b7881136ffdeec8/examples_jupyter.zip

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‎refactor_development_regularization_cocktails/_modules/autoPyTorch/api/tabular_classification.html

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<p>
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&copy; Copyright 2014-2019, Machine Learning Professorship Freiburg.<br/>
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Created using <a href="http://sphinx-doc.org/">Sphinx</a> 3.5.2.<br/>
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Created using <a href="http://sphinx-doc.org/">Sphinx</a> 3.5.3.<br/>
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</p>
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</footer>

‎refactor_development_regularization_cocktails/_modules/index.html

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</p>
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<p>
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&copy; Copyright 2014-2019, Machine Learning Professorship Freiburg.<br/>
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Created using <a href="http://sphinx-doc.org/">Sphinx</a> 3.5.2.<br/>
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Created using <a href="http://sphinx-doc.org/">Sphinx</a> 3.5.3.<br/>
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</p>
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</div>
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</footer>

‎refactor_development_regularization_cocktails/_sources/examples/example_image_classification.rst.txt

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‎refactor_development_regularization_cocktails/_sources/examples/example_tabular_classification.rst.txt

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.. code-block:: none
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<smac.runhistory.runhistory.RunHistory object at 0x7f9add238610> [TrajEntry(train_perf=2147483648, incumbent_id=1, incumbent=Configuration:
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<smac.runhistory.runhistory.RunHistory object at 0x7f65d474acd0> [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'
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optimizer:AdamOptimizer:beta2, Value: 0.9
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optimizer:AdamOptimizer:lr, Value: 0.01
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optimizer:AdamOptimizer:use_weight_decay, Value: True
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optimizer:AdamOptimizer:weight_decay, Value: 0.0
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optimizer:AdamOptimizer:weight_decay, Value: 0.0001
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optimizer:__choice__, Value: 'AdamOptimizer'
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scaler:__choice__, Value: 'StandardScaler'
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trainer:StandardTrainer:Lookahead:la_alpha, Value: 0.6
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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=0.0023033618927001953, 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=0.0023374557495117188, 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'
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optimizer:AdamOptimizer:beta2, Value: 0.9
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optimizer:AdamOptimizer:lr, Value: 0.01
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optimizer:AdamOptimizer:use_weight_decay, Value: True
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optimizer:AdamOptimizer:weight_decay, Value: 0.0
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optimizer:AdamOptimizer:weight_decay, Value: 0.0001
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optimizer:__choice__, Value: 'AdamOptimizer'
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scaler:__choice__, Value: 'StandardScaler'
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trainer:StandardTrainer:Lookahead:la_alpha, Value: 0.6
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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=5.061767578125, wallclock_time=6.761995077133179, budget=5.555555555555555), TrajEntry(train_perf=0.15204678362573099, incumbent_id=2, incumbent=Configuration:
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, ta_runs=1, ta_time_used=5.916302919387817, wallclock_time=7.4252846240997314, budget=5.555555555555555), TrajEntry(train_perf=0.14035087719298245, incumbent_id=2, incumbent=Configuration:
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data_loader:batch_size, Value: 75
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encoder:__choice__, Value: 'OneHotEncoder'
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feature_preprocessor:RandomKitchenSinks:gamma, Value: 0.013010719396102707
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network_backbone:ResNetBackbone:blocks_per_group_1, Value: 3
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network_backbone:ResNetBackbone:multi_branch_choice, Value: 'shake-shake'
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network_backbone:ResNetBackbone:num_groups, Value: 1
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network_backbone:ResNetBackbone:num_units_0, Value: 891
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network_backbone:ResNetBackbone:num_units_1, Value: 534
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network_backbone:ResNetBackbone:num_units_0, Value: 553
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network_backbone:ResNetBackbone:num_units_1, Value: 107
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network_backbone:ResNetBackbone:use_batch_norm, Value: False
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network_backbone:ResNetBackbone:use_dropout, Value: False
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network_backbone:ResNetBackbone:use_skip_connection, Value: True
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optimizer:RMSpropOptimizer:lr, Value: 0.016961171655317835
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optimizer:RMSpropOptimizer:momentum, Value: 0.7920241884670927
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optimizer:RMSpropOptimizer:use_weight_decay, Value: True
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optimizer:RMSpropOptimizer:weight_decay, Value: 0.032552201041967745
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optimizer:RMSpropOptimizer:weight_decay, Value: 8.977017307979806e-06
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optimizer:__choice__, Value: 'RMSpropOptimizer'
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scaler:Normalizer:norm, Value: 'mean_squared'
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scaler:__choice__, Value: 'Normalizer'
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trainer:MixUpTrainer:use_stochastic_weight_averaging, Value: False
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trainer:MixUpTrainer:weighted_loss, Value: False
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trainer:__choice__, Value: 'MixUpTrainer'
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, ta_runs=19, ta_time_used=214.1450550556183, wallclock_time=279.02319598197937, budget=50.0), TrajEntry(train_perf=0.11695906432748537, incumbent_id=3, incumbent=Configuration:
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data_loader:batch_size, Value: 222
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encoder:__choice__, Value: 'OneHotEncoder'
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feature_preprocessor:Nystroem:kernel, Value: 'cosine'
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feature_preprocessor:Nystroem:n_components, Value: 6
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feature_preprocessor:__choice__, Value: 'Nystroem'
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imputer:categorical_strategy, Value: 'most_frequent'
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imputer:numerical_strategy, Value: 'most_frequent'
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lr_scheduler:__choice__, Value: 'NoScheduler'
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network_backbone:ShapedResNetBackbone:activation, Value: 'relu'
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network_backbone:ShapedResNetBackbone:blocks_per_group, Value: 2
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network_backbone:ShapedResNetBackbone:max_units, Value: 793
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network_backbone:ShapedResNetBackbone:multi_branch_choice, Value: 'shake-shake'
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network_backbone:ShapedResNetBackbone:num_groups, Value: 1
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network_backbone:ShapedResNetBackbone:output_dim, Value: 408
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network_backbone:ShapedResNetBackbone:resnet_shape, Value: 'diamond'
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network_backbone:ShapedResNetBackbone:use_batch_norm, Value: True
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network_backbone:ShapedResNetBackbone:use_dropout, Value: False
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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:activation, Value: 'relu'
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network_head:fully_connected:num_layers, Value: 2
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network_head:fully_connected:units_layer_1, Value: 342
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network_init:NoInit:bias_strategy, Value: 'Normal'
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network_init:__choice__, Value: 'NoInit'
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optimizer:RMSpropOptimizer:alpha, Value: 0.31508999898669854
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optimizer:RMSpropOptimizer:lr, Value: 0.000141083113558384
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optimizer:RMSpropOptimizer:momentum, Value: 0.4310565312768747
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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: 'mean_squared'
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scaler:__choice__, Value: 'Normalizer'
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trainer:AdversarialTrainer:epsilon, Value: 0.13573947533310454
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trainer:AdversarialTrainer:se_lastk, Constant: 3
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trainer:AdversarialTrainer:use_lookahead_optimizer, Value: False
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trainer:AdversarialTrainer:use_snapshot_ensemble, Value: True
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trainer:AdversarialTrainer:use_stochastic_weight_averaging, Value: True
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trainer:AdversarialTrainer:weighted_loss, Value: False
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trainer:__choice__, Value: 'AdversarialTrainer'
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, ta_runs=20, ta_time_used=233.27314519882202, wallclock_time=302.0042383670807, budget=50.0)]
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{'accuracy': 0.8959537572254336}
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, ta_runs=19, ta_time_used=204.9274971485138, wallclock_time=272.3745219707489, budget=50.0)]
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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 | 0.34 |
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| 1 | SimpleImputer,NoEncoder,Normalizer,NoFeaturePreprocessing | no embedding,ShapedResNetBackbone,FullyConnectedHead,nn.Sequential | 0.16 |
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| 2 | SimpleImputer,OneHotEncoder,Normalizer,Nystroem | no embedding,ShapedResNetBackbone,FullyConnectedHead,nn.Sequential | 0.16 |
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| 3 | SimpleImputer,OneHotEncoder,StandardScaler,TruncSVD | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.12 |
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| 4 | SimpleImputer,OneHotEncoder,Normalizer,KitchenSink | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.12 |
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| 5 | SimpleImputer,OneHotEncoder,StandardScaler,Nystroem | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
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| 6 | None | KNNClassifier | 0.02 |
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| 7 | None | RFClassifier | 0.02 |
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| 8 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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| 1 | None | RFClassifier | 0.14 |
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| 2 | SimpleImputer,OneHotEncoder,Normalizer,KernelPCA | embedding,MLPBackbone,FullyConnectedHead,nn.Sequential | 0.1 |
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| 3 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.1 |
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| 4 | SimpleImputer,OneHotEncoder,StandardScaler,PolynomialFeatures | embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.08 |
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| 5 | SimpleImputer,OneHotEncoder,Normalizer,KitchenSink | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.08 |
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| 6 | SimpleImputer,OneHotEncoder,Normalizer,Nystroem | no embedding,ShapedResNetBackbone,FullyConnectedHead,nn.Sequential | 0.04 |
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| 7 | None | KNNClassifier | 0.04 |
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| 8 | SimpleImputer,OneHotEncoder,StandardScaler,Nystroem | no embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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| 9 | SimpleImputer,OneHotEncoder,StandardScaler,PowerTransformer | embedding,ResNetBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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| 10 | None | SVC | 0.02 |
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| 11 | SimpleImputer,OneHotEncoder,StandardScaler,NoFeaturePreprocessing | embedding,ShapedMLPBackbone,FullyConnectedHead,nn.Sequential | 0.02 |
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**Total running time of the script:** ( 9 minutes 24.694 seconds)
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.. _sphx_glr_download_examples_example_tabular_classification.py:

‎refactor_development_regularization_cocktails/_sources/examples/example_tabular_regression.rst.txt

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, ta_runs=0, ta_time_used=0.0, wallclock_time=0.001964092254638672, budget=0), TrajEntry(train_perf=0.0008204224883585631, incumbent_id=1, incumbent=Configuration:
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imputer:numerical_strategy, Value: 'most_frequent'
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optimizer:AdamOptimizer:beta1, Value: 0.9481379615749385
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optimizer:AdamOptimizer:beta2, Value: 0.975978385169487
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optimizer:AdamOptimizer:lr, Value: 0.01924341974264098
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optimizer:AdamOptimizer:use_weight_decay, Value: False
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optimizer:__choice__, Value: 'AdamOptimizer'
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scaler:__choice__, Value: 'NoScaler'
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trainer:MixUpTrainer:alpha, Value: 0.6106245467721916
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trainer:MixUpTrainer:use_lookahead_optimizer, Value: False
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{'r2': 0.9996698482299967}
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, ta_runs=1, ta_time_used=9.31979751586914, wallclock_time=13.245802164077759, budget=5.555555555555555)]
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{'r2': 0.9995805604515139}
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**Total running time of the script:** ( 8 minutes 34.566 seconds)
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.. _sphx_glr_download_examples_example_tabular_regression.py:

‎refactor_development_regularization_cocktails/_sources/examples/sg_execution_times.rst.txt

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=================
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**18:07.029** total execution time for **examples** files:
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| :ref:`sphx_glr_examples_example_tabular_classification.py` (``example_tabular_classification.py``) | 09:20.536 | 0.0 MB |
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| :ref:`sphx_glr_examples_example_tabular_classification.py` (``example_tabular_classification.py``) | 09:24.694 | 0.0 MB |
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| :ref:`sphx_glr_examples_example_tabular_regression.py` (``example_tabular_regression.py``) | 08:35.774 | 0.0 MB |
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| :ref:`sphx_glr_examples_example_tabular_regression.py` (``example_tabular_regression.py``) | 08:34.566 | 0.0 MB |
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+----------------------------------------------------------------------------------------------------+-----------+--------+
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| :ref:`sphx_glr_examples_example_image_classification.py` (``example_image_classification.py``) | 00:09.811 | 0.0 MB |
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| :ref:`sphx_glr_examples_example_image_classification.py` (``example_image_classification.py``) | 00:07.768 | 0.0 MB |
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+----------------------------------------------------------------------------------------------------+-----------+--------+

‎refactor_development_regularization_cocktails/api.html

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&copy; Copyright 2014-2019, Machine Learning Professorship Freiburg.<br/>
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Created using <a href="http://sphinx-doc.org/">Sphinx</a> 3.5.2.<br/>
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Created using <a href="http://sphinx-doc.org/">Sphinx</a> 3.5.3.<br/>
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