DEVELOPMENT... OpenML
Flow
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,classifier=sklearn.svm.classes.SVC))

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,classifier=sklearn.svm.classes.SVC))

Visibility: public Uploaded 13-01-2018 by Jasmine Robinson 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.

Components

estimatorsklearn.pipeline.Pipeline(imputation=mylib.preprocessing_openml14.ConditionalImputer,one_hot_encoder=sklearn.preprocessing.data.OneHotEncoder,variance-thresholding=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)(1)

Parameters

cvdefault: 3
error_scoredefault: "raise"
estimatordefault: {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": null}}
fit_paramsdefault: null
iiddefault: true
n_iterdefault: 50
n_jobsdefault: -1
param_distributionsdefault: {"classifier__C": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "mylib.distributions.loguniform_gen", "a": 0.03125, "b": 32768, "args": [], "kwds": {"base": 2, "low": 0.03125, "high": 32768}}}, "classifier__gamma": {"oml-python:serialized_object": "rv_frozen", "value": {"dist": "mylib.distributions.loguniform_gen", "a": 3.0517578125e-05, "b": 8, "args": [], "kwds": {"base": 2, "low": 3.0517578125e-05, "high": 8}}}, "classifier__shrinking": [true, false], "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}}}, "imputation__strategy": ["mean", "median", "most_frequent"]}
pre_dispatchdefault: "2*n_jobs"
random_statedefault: 1
refitdefault: true
return_train_scoredefault: "warn"
scoringdefault: null
verbosedefault: 0

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