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arbok.autosklearn.AutoSklearnWrapper(preprocessor=sklearn.pipeline.Pipeline(conditionalimputer=arbok.preprocessing.ConditionalImputer,onehotencoder=sklearn.preprocessing.data.OneHotEncoder))

arbok.autosklearn.AutoSklearnWrapper(preprocessor=sklearn.pipeline.Pipeline(conditionalimputer=arbok.preprocessing.ConditionalImputer,onehotencoder=sklearn.preprocessing.data.OneHotEncoder))

Visibility: public Uploaded 24-05-2018 by Michael Torres sklearn==0.19.1 numpy>=1.6.1 scipy>=0.9 1 runs
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  • openml-python python scikit-learn sklearn sklearn_0.19.1
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Automatically created scikit-learn flow.

Components

Parameters

delete_output_folder_after_terminatedefault: true
delete_tmp_folder_after_terminatedefault: true
disable_evaluator_outputdefault: false
ensemble_nbestdefault: 50
ensemble_sizedefault: 50
exclude_estimatorsdefault: null
exclude_preprocessorsdefault: null
get_smac_object_callbackdefault: null
include_estimatorsdefault: null
include_preprocessorsdefault: null
initial_configurations_via_metalearningdefault: 25
ml_memory_limitdefault: 3072
output_folderdefault: null
per_run_time_limitdefault: 20
preprocessordefault: {"oml-python:serialized_object": "component_reference", "value": {"key": "preprocessor", "step_name": null}}
refitdefault: true
resampling_strategydefault: "holdout"
resampling_strategy_argumentsdefault: null
retry_on_errordefault: false
seeddefault: 1
shared_modedefault: false
smac_scenario_argsdefault: null
time_left_for_this_taskdefault: 20
tmp_folderdefault: null
verbosedefault: true

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