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

Visibility: public Uploaded 13-05-2018 by Michael Torres sklearn==0.19.1 numpy>=1.6.1 scipy>=0.9 1 runs
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Automatically created scikit-learn flow.

Components

preprocessor

sklearn.pipeline.Pipeline(conditionalimputer=arbok.preprocessing.ConditionalImputer,onehotencoder=sklearn.preprocessing.data.OneHotEncoder)(1)

Parameters

crossover_rate		default: 0.1
cv		default: 5
disable_update_check		default: false
early_stop		default: null
generations		default: 2
max_eval_time_mins		default: 5
max_time_mins		default: null
memory		default: null
mutation_rate		default: 0.9
n_jobs		default: 1
offspring_size		default: 2
periodic_checkpoint_folder		default: null
population_size		default: 2
preprocessor		default: {"oml-python:serialized_object": "component_reference", "value": {"key": "preprocessor", "step_name": null}}
random_state		default: null
refit		default: true
retry_on_error		default: true
scoring		default: null
subsample		default: 1.0
verbose		default: true
verbosity		default: 2
warm_start		default: false

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

Components

Parameters

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