Run 10458076

Task 9981 (Supervised Classification) cnae-9 Uploaded 19-05-2020 by Marc Zöller
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sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._fastica.FastICA,ste p_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	0.7971213689742238
sklearn.tree._classes.DecisionTreeClassifier(3)_class_weight	null
sklearn.tree._classes.DecisionTreeClassifier(3)_criterion	"gini"
sklearn.tree._classes.DecisionTreeClassifier(3)_max_depth	245
sklearn.tree._classes.DecisionTreeClassifier(3)_max_features	0.47587806975702124
sklearn.tree._classes.DecisionTreeClassifier(3)_max_leaf_nodes	2
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_decrease	0.0988003174957179
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_split	null
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_leaf	0.17068794078309812
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_split	0.43839530407286065
sklearn.tree._classes.DecisionTreeClassifier(3)_min_weight_fraction_leaf	0.05373852812865315
sklearn.tree._classes.DecisionTreeClassifier(3)_presort	"deprecated"
sklearn.tree._classes.DecisionTreeClassifier(3)_random_state	42
sklearn.tree._classes.DecisionTreeClassifier(3)_splitter	"best"
sklearn.decomposition._fastica.FastICA(1)_algorithm	"parallel"
sklearn.decomposition._fastica.FastICA(1)_fun	"logcosh"
sklearn.decomposition._fastica.FastICA(1)_fun_args	null
sklearn.decomposition._fastica.FastICA(1)_max_iter	677
sklearn.decomposition._fastica.FastICA(1)_n_components	89
sklearn.decomposition._fastica.FastICA(1)_random_state	42
sklearn.decomposition._fastica.FastICA(1)_tol	0.6774115937469003
sklearn.decomposition._fastica.FastICA(1)_w_init	null
sklearn.decomposition._fastica.FastICA(1)_whiten	false
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._fastica.FastICA,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_memory	null
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._fastica.FastICA,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.decomposition._fastica.FastICA,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_verbose	false