DEVELOPMENT... OpenML
Flow
sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.LinearSVC)

sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one-hot-encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,feature-scaling=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.svm.classes.LinearSVC)

Visibility: public Uploaded 24-01-2018 by Jasmine Robinson sklearn==0.19.1 numpy>=1.6.1 scipy>=0.9 0 runs
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  • 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": "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": "feature-scaling", "step_name": "feature-scaling"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "classifier", "step_name": "classifier"}}]

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