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sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one_hot_encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,standardization=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.neural_network.multilayer_perceptron.MLPClassifier))

sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one_hot_encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,standardization=sklearn.preprocessing.data.StandardScaler,classifier=sklearn.neural_network.multilayer_perceptron.MLPClassifier))

Visibility: public Uploaded 10-11-2017 by Jasmine Robinson 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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Parameters

cvdefault: 2
error_scoredefault: "raise"
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: {"classifier__alpha": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "mylib.distributions.loguniform_gen", "a": 1e-07, "b": 0.0001, "args": [], "kwds": {"base": 10, "low": 1e-07, "high": 0.0001}}}, "classifier__tol": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "mylib.distributions.loguniform_gen", "a": 1e-05, "b": 0.1, "args": [], "kwds": {"base": 2, "low": 1e-05, "high": 0.1}}}}
pre_dispatchdefault: "2*n_jobs"
random_statedefault: 1
refitdefault: true
return_train_scoredefault: true
scoringdefault: null
verbosedefault: 0

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