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Task 2297 (Supervised Regression) triazines Uploaded 11-01-2019 by Nico Strasdat
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sklearn.pipeline.Pipeline(missing=sklearn.impute.SimpleImputer,scale=sklear n.preprocessing.data.StandardScaler,predict=hpo4svm.hpo.SVR)(1)	Automatically created scikit-learn flow.
sklearn.preprocessing.data.StandardScaler(18)_copy	true
sklearn.preprocessing.data.StandardScaler(18)_with_mean	true
sklearn.preprocessing.data.StandardScaler(18)_with_std	true
sklearn.impute.SimpleImputer(3)_copy	true
sklearn.impute.SimpleImputer(3)_fill_value	null
sklearn.impute.SimpleImputer(3)_missing_values	NaN
sklearn.impute.SimpleImputer(3)_strategy	"mean"
sklearn.impute.SimpleImputer(3)_verbose	0
sklearn.pipeline.Pipeline(missing=sklearn.impute.SimpleImputer,scale=sklearn.preprocessing.data.StandardScaler,predict=hpo4svm.hpo.SVR)(1)_memory	null
hpo4svm.hpo.SVR(1)_options	[{"kernel_type": "rbf", "lb": {"lmbda": 1e-06}, "n_cv": 5, "problem_type": "regression", "to_optimize": ["lmbda", "gamma"], "tol": 1e-06, "ub": {}}]
hpo4svm.hpo.SVR(1)_params	{"delta": 0.1, "epsilon": 0.0, "gamma": 0.1, "lmbda": 1.0, "nu": 0.05}