DEVELOPMENT... OpenML
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sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.ensemble.forest.RandomForestClassifier))

sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.ensemble.forest.RandomForestClassifier))

Visibility: public Uploaded 13-03-2017 by Christopher Black sklearn==0.18.1 numpy>=1.6.1 scipy>=0.9 4 runs
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  • Verified_Supervised_Classification
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Automatically created sub-component.

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Parameters

cvdefault: 10
error_scoredefault: "raise"
estimatordefault: {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": null}}
fit_params
iiddefault: true
n_jobsdefault: -1
param_griddefault: {"Classifier__n_estimators": [8, 32, 128, 512]}
pre_dispatchdefault: "2*n_jobs"
refitdefault: true
return_train_scoredefault: true
scoringdefault: "roc_auc"
verbosedefault: 0

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