Flow
arbok.tpot.TPOTWrapper(preprocessor=sklearn.pipeline.Pipeline(conditionalimputer=arbok.preprocessing.ConditionalImputer,onehotencoder=sklearn.preprocessing.data.OneHotEncoder,variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold))

arbok.tpot.TPOTWrapper(preprocessor=sklearn.pipeline.Pipeline(conditionalimputer=arbok.preprocessing.ConditionalImputer,onehotencoder=sklearn.preprocessing.data.OneHotEncoder,variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold))

Visibility: public Uploaded 28-05-2018 by Jeroen van Hoof sklearn==0.19.1 numpy>=1.6.1 scipy>=0.9 18 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

crossover_ratedefault: 0.1
cvdefault: 5
disable_update_checkdefault: false
early_stopdefault: null
generationsdefault: 1000000
max_eval_time_minsdefault: 5
max_time_minsdefault: 60
memorydefault: null
mutation_ratedefault: 0.9
n_jobsdefault: 1
offspring_sizedefault: 100
periodic_checkpoint_folderdefault: null
population_sizedefault: 100
preprocessordefault: {"oml-python:serialized_object": "component_reference", "value": {"key": "preprocessor", "step_name": null}}
random_statedefault: null
refitdefault: true
retry_on_errordefault: false
scoringdefault: null
subsampledefault: 1.0
verbosedefault: true
verbositydefault: 0
warm_startdefault: false

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