Flow
sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.ExtraTreesClassifier,voting=sklearn.ensemble.forest.RandomForestClassifier),voting=sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,voting=xgboost.sklearn.XGBClassifier))

sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.ExtraTreesClassifier,voting=sklearn.ensemble.forest.RandomForestClassifier),voting=sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,voting=xgboost.sklearn.XGBClassifier))

Visibility: public Uploaded 13-03-2017 by Joost Visser sklearn==0.18.1 numpy>=1.6.1 scipy>=0.9 0 runs
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Automatically created scikit-learn flow.

Components

estimatorssklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.ExtraTreesClassifier,voting=sklearn.ensemble.forest.RandomForestClassifier)(1)
votingsklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,voting=xgboost.sklearn.XGBClassifier)(1)

Parameters

estimatorsdefault: [{"oml-python:serialized_object": "component_reference", "value": {"key": "estimators", "step_name": "estimators"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "voting", "step_name": "voting"}}]
n_jobsdefault: -1
votingdefault: "soft"
weightsdefault: null

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