Flow
sklearn.ensemble.voting_classifier.VotingClassifier(svc=sklearn.svm.classes.SVC,kn=sklearn.neighbors.classification.KNeighborsClassifier,gnb=sklearn.naive_bayes.GaussianNB,logreg=sklearn.pipeline.Pipeline(Scaler=sklearn.preprocessing.data.Normalizer,Classifier=sklearn.linear_model.logistic.LogisticRegression),xgb=xgboost.sklearn.XGBClassifier)

sklearn.ensemble.voting_classifier.VotingClassifier(svc=sklearn.svm.classes.SVC,kn=sklearn.neighbors.classification.KNeighborsClassifier,gnb=sklearn.naive_bayes.GaussianNB,logreg=sklearn.pipeline.Pipeline(Scaler=sklearn.preprocessing.data.Normalizer,Classifier=sklearn.linear_model.logistic.LogisticRegression),xgb=xgboost.sklearn.XGBClassifier)

Visibility: public Uploaded 15-03-2018 by Maarten van Asseldonk 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

estimatorsdefault: [{"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "kn", "step_name": "kn"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gnb", "step_name": "gnb"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "logreg", "step_name": "logreg"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "xgb", "step_name": "xgb"}}]
flatten_transformdefault: null
n_jobsdefault: -1
votingdefault: "soft"
weightsdefault: [4, 1, 1, 1, 1]

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