Flow
openmldefaults.search.default_search.DefaultSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)))

openmldefaults.search.default_search.DefaultSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)))

Visibility: public Uploaded 28-07-2018 by Jan van Rijn sklearn==0.18.1 numpy>=1.6.1 scipy>=0.9 0 runs
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  • openml-python python scikit-learn sklearn sklearn_0.18.1
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Automatically created scikit-learn flow.

Components

Parameters

cvdefault: null
defaultsdefault: [{"classifier__algorithm": "SAMME", "classifier__base_estimator__max_depth": 8, "classifier__learning_rate": 0.4401420420561976, "classifier__n_estimators": 371, "imputation__strategy": "median"}]
error_scoredefault: "raise"
estimatordefault: {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": null}}
fit_params
iiddefault: "warn"
n_jobsdefault: -1
pre_dispatchdefault: "2*n_jobs"
refitdefault: true
return_train_scoredefault: "warn"
scoringdefault: "accuracy"
verbosedefault: 0

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