Run 10457944

Task 9981 (Supervised Classification) cnae-9 Uploaded 19-05-2020 by Marc Zöller
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sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._data.QuantileTransf ormer,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)	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 it to 'passthrough' or ``None``.
sklearn.tree._classes.DecisionTreeClassifier(3)_ccp_alpha	0.32884260814244326
sklearn.tree._classes.DecisionTreeClassifier(3)_class_weight	null
sklearn.tree._classes.DecisionTreeClassifier(3)_criterion	"entropy"
sklearn.tree._classes.DecisionTreeClassifier(3)_max_depth	53
sklearn.tree._classes.DecisionTreeClassifier(3)_max_features	0.13690244779521296
sklearn.tree._classes.DecisionTreeClassifier(3)_max_leaf_nodes	34
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_decrease	0.13825217901572853
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_split	null
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_leaf	0.01632774975179226
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_split	0.26543519178728897
sklearn.tree._classes.DecisionTreeClassifier(3)_min_weight_fraction_leaf	0.4983223638250338
sklearn.tree._classes.DecisionTreeClassifier(3)_presort	"deprecated"
sklearn.tree._classes.DecisionTreeClassifier(3)_random_state	42
sklearn.tree._classes.DecisionTreeClassifier(3)_splitter	"random"
sklearn.preprocessing._data.QuantileTransformer(1)_copy	false
sklearn.preprocessing._data.QuantileTransformer(1)_ignore_implicit_zeros	false
sklearn.preprocessing._data.QuantileTransformer(1)_n_quantiles	959
sklearn.preprocessing._data.QuantileTransformer(1)_output_distribution	"normal"
sklearn.preprocessing._data.QuantileTransformer(1)_random_state	42
sklearn.preprocessing._data.QuantileTransformer(1)_subsample	18922588
sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._data.QuantileTransformer,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_memory	null
sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._data.QuantileTransformer,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_steps	[{"oml-python:serialized_object": "component_reference", "value": {"key": "step_0", "step_name": "step_0"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "step_1", "step_name": "step_1"}}]
sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._data.QuantileTransformer,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_verbose	false