Flow
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputer=Preprocessing.preprocessingOpenML14.ConditionalImputer,one_hot_encoder=sklearn.preprocessing.data.OneHotEncoder,standardization=sklearn.preprocessing.data.StandardScaler,variance-thresholding=Preprocessing.preprocessingOpenML14.MemoryEfficientVarianceThreshold,estimator=sklearn.svm.classes.SVC))

sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputer=Preprocessing.preprocessingOpenML14.ConditionalImputer,one_hot_encoder=sklearn.preprocessing.data.OneHotEncoder,standardization=sklearn.preprocessing.data.StandardScaler,variance-thresholding=Preprocessing.preprocessingOpenML14.MemoryEfficientVarianceThreshold,estimator=sklearn.svm.classes.SVC))

Visibility: public Uploaded 05-10-2017 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_0.19.0
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Automatically created scikit-learn flow.

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cvdefault: 2
error_scoredefault: 0
estimatordefault: {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": null}}
fit_paramsdefault: null
iiddefault: true
n_iterdefault: 1
n_jobsdefault: 1
param_distributionsdefault: {"estimator__C": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "Distributions.loguniform.loguniform_gen", "a": 0.03125, "b": 32768, "args": [], "kwds": {"base": 2, "low": 0.03125, "high": 32768}}}, "estimator__shrinking": [true, false], "imputer__strategy": ["mean", "median", "most_frequent"]}
pre_dispatchdefault: "2*n_jobs"
random_statedefault: null
refitdefault: true
return_train_scoredefault: true
scoringdefault: null
verbosedefault: 0

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