DEVELOPMENT... OpenML
Flow
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)

sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)

Visibility: public Uploaded 22-11-2017 by Jason 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.

Parameters

stepsdefault: [{"oml-python:serialized_object": "component_reference", "value": {"key": "imputation", "step_name": "imputation"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "hotencoding", "step_name": "hotencoding"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variencethreshold", "step_name": "variencethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "scaling", "step_name": "scaling"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "classifier", "step_name": "classifier"}}]

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