Flow
sklearn.pipeline.Pipeline(imputer=Preprocessing.preprocessingOpenML14.ConditionalImputer,one_hot_encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,standardization=sklearn.preprocessing.data.StandardScaler,estimator=sklearn.neural_network.multilayer_perceptron.MLPClassifier)

sklearn.pipeline.Pipeline(imputer=Preprocessing.preprocessingOpenML14.ConditionalImputer,one_hot_encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,standardization=sklearn.preprocessing.data.StandardScaler,estimator=sklearn.neural_network.multilayer_perceptron.MLPClassifier)

Visibility: public Uploaded 04-11-2017 by Benjamin Strang sklearn==0.19.0 numpy>=1.6.1 scipy>=0.9 0 runs
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  • openml-python python scikit-learn sklearn sklearn_0190
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Automatically created scikit-learn flow.

Parameters

memorydefault: null
stepsdefault: [{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "one_hot_encoder", "step_name": "one_hot_encoder"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variance-thresholding", "step_name": "variance-thresholding"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardization", "step_name": "standardization"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": "estimator"}}]

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