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Task 10093 (Supervised Classification) banknote-authentication Uploaded 31-03-2020 by Nicolas Hug
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sklearn.calibration.CalibratedClassifierCV(base_estimator=sklearn.pipeline. Pipeline(standardscaler=sklearn.preprocessing._data.StandardScaler,svc=skle arn.svm._classes.SVC))(2)	Probability calibration with isotonic regression or logistic regression. The calibration is based on the :term:`decision_function` method of the `base_estimator` if it exists, else on :term:`predict_proba`.
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing._data.StandardScaler,svc=sklearn.svm._classes.SVC)(2)_memory	null
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing._data.StandardScaler,svc=sklearn.svm._classes.SVC)(2)_steps	[{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing._data.StandardScaler,svc=sklearn.svm._classes.SVC)(2)_verbose	false
sklearn.preprocessing._data.StandardScaler(3)_copy	true
sklearn.preprocessing._data.StandardScaler(3)_with_mean	true
sklearn.preprocessing._data.StandardScaler(3)_with_std	true
sklearn.svm._classes.SVC(3)_C	1.0
sklearn.svm._classes.SVC(3)_break_ties	false
sklearn.svm._classes.SVC(3)_cache_size	200
sklearn.svm._classes.SVC(3)_class_weight	null
sklearn.svm._classes.SVC(3)_coef0	0.0
sklearn.svm._classes.SVC(3)_decision_function_shape	"ovr"
sklearn.svm._classes.SVC(3)_degree	3
sklearn.svm._classes.SVC(3)_gamma	"scale"
sklearn.svm._classes.SVC(3)_kernel	"linear"
sklearn.svm._classes.SVC(3)_max_iter	-1
sklearn.svm._classes.SVC(3)_probability	false
sklearn.svm._classes.SVC(3)_random_state	53226
sklearn.svm._classes.SVC(3)_shrinking	true
sklearn.svm._classes.SVC(3)_tol	0.001
sklearn.svm._classes.SVC(3)_verbose	false
sklearn.calibration.CalibratedClassifierCV(base_estimator=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing._data.StandardScaler,svc=sklearn.svm._classes.SVC))(2)_cv	5
sklearn.calibration.CalibratedClassifierCV(base_estimator=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing._data.StandardScaler,svc=sklearn.svm._classes.SVC))(2)_method	"sigmoid"