Flow
sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.svm.classes.SVC)

sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.svm.classes.SVC)

Visibility: public Uploaded 28-03-2018 by Hilde Weerts sklearn==0.19.1 numpy>=1.6.1 scipy>=0.9 75800 runs
0 likes downloaded by 1 people 0 issues 0 downvotes , 1 total downloads
  • openml-python python scikit-learn sklearn sklearn_0.19.1
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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": "scaling", "step_name": "scaling"}}, {"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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