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

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

Visibility: public Uploaded 16-05-2018 by Jeroen van Hoof sklearn==0.19.1 numpy>=1.6.1 scipy>=0.9 24 runs
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
  • openml-python python scikit-learn sklearn sklearn_0.19.1
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
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: 1
max_time_minsdefault: 6
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: true
scoringdefault: null
subsampledefault: 1.0
verbosedefault: false
verbositydefault: 0
warm_startdefault: false

0
Runs

List all runs
Parameter:
Rendering chart
Rendering table