Run 10560534

Task 167141 (Supervised Classification) churn Uploaded 14-08-2021 by Sergey Redyuk
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sklearn.pipeline.Pipeline(robustscaler=sklearn.preprocessing.data.RobustSca ler,kneighborsclassifier=sklearn.neighbors.classification.KNeighborsClassif ier)(2)	Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit and transform methods. The final estimator only needs to implement fit. The transformers in the pipeline can be cached using ``memory`` argument. The purpose of the pipeline is to assemble several steps that can be cross-validated together while setting different parameters. For this, it enables setting parameters of the various steps using their names and the parameter name separated by a '__', as in the example below. A step's estimator may be replaced entirely by setting the parameter with its name to another estimator, or a transformer removed by setting to None.
sklearn.neighbors.classification.KNeighborsClassifier(45)_algorithm	"auto"
sklearn.neighbors.classification.KNeighborsClassifier(45)_leaf_size	30
sklearn.neighbors.classification.KNeighborsClassifier(45)_metric	"minkowski"
sklearn.neighbors.classification.KNeighborsClassifier(45)_metric_params	null
sklearn.neighbors.classification.KNeighborsClassifier(45)_n_jobs	1
sklearn.neighbors.classification.KNeighborsClassifier(45)_n_neighbors	5
sklearn.neighbors.classification.KNeighborsClassifier(45)_p	2
sklearn.neighbors.classification.KNeighborsClassifier(45)_weights	"uniform"
sklearn.pipeline.Pipeline(robustscaler=sklearn.preprocessing.data.RobustScaler,kneighborsclassifier=sklearn.neighbors.classification.KNeighborsClassifier)(2)_memory	null
sklearn.pipeline.Pipeline(robustscaler=sklearn.preprocessing.data.RobustScaler,kneighborsclassifier=sklearn.neighbors.classification.KNeighborsClassifier)(2)_steps	[{"oml-python:serialized_object": "component_reference", "value": {"key": "robustscaler", "step_name": "robustscaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "kneighborsclassifier", "step_name": "kneighborsclassifier"}}]
sklearn.preprocessing.data.RobustScaler(6)_copy	true
sklearn.preprocessing.data.RobustScaler(6)_quantile_range	[25.0, 75.0]
sklearn.preprocessing.data.RobustScaler(6)_with_centering	true
sklearn.preprocessing.data.RobustScaler(6)_with_scaling	true