Flow
sklearn.pipeline.Pipeline(imputation=preprocessing.ConditionalImputer2,hotencoding=sklearn.preprocessing._encoders.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.ensemble.forest.RandomForestClassifier)

sklearn.pipeline.Pipeline(imputation=preprocessing.ConditionalImputer2,hotencoding=sklearn.preprocessing._encoders.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.ensemble.forest.RandomForestClassifier)

Visibility: public Uploaded 24-12-2018 by Pieter Gijsbers sklearn==0.20.0 numpy>=1.6.1 scipy>=0.9 1 runs
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  • openml-python python scikit-learn sklearn sklearn_0.20.0
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Automatically created scikit-learn flow.

Parameters

memorydefault: null
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": "clf", "step_name": "clf"}}]

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