Run 10462108

Task 3891 (Supervised Classification) gina_agnostic Uploaded 20-05-2020 by Marc Zöller
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads

Issue	#Downvotes for this reason	By

Flow

sklearn.pipeline.Pipeline(step_0=sklearn.feature_selection._univariate_sele ction.GenericUnivariateSelect,step_1=sklearn.tree._classes.DecisionTreeClas sifier)(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	0.2684201880801075
sklearn.tree._classes.DecisionTreeClassifier(3)_class_weight	null
sklearn.tree._classes.DecisionTreeClassifier(3)_criterion	"gini"
sklearn.tree._classes.DecisionTreeClassifier(3)_max_depth	500
sklearn.tree._classes.DecisionTreeClassifier(3)_max_features	0.6055425797560658
sklearn.tree._classes.DecisionTreeClassifier(3)_max_leaf_nodes	3197
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_decrease	0.16786349163361175
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_split	null
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_leaf	0.39919498798607767
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_split	0.26373824584634387
sklearn.tree._classes.DecisionTreeClassifier(3)_min_weight_fraction_leaf	0.3409975364197552
sklearn.tree._classes.DecisionTreeClassifier(3)_presort	"deprecated"
sklearn.tree._classes.DecisionTreeClassifier(3)_random_state	42
sklearn.tree._classes.DecisionTreeClassifier(3)_splitter	"best"
sklearn.feature_selection._univariate_selection.GenericUnivariateSelect(1)_mode	"fdr"
sklearn.feature_selection._univariate_selection.GenericUnivariateSelect(1)_param	0.41665016240906816
sklearn.feature_selection._univariate_selection.GenericUnivariateSelect(1)_score_func	{"oml-python:serialized_object": "function", "value": "sklearn.feature_selection._univariate_selection.f_classif"}
sklearn.pipeline.Pipeline(step_0=sklearn.feature_selection._univariate_selection.GenericUnivariateSelect,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_memory	null
sklearn.pipeline.Pipeline(step_0=sklearn.feature_selection._univariate_selection.GenericUnivariateSelect,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.feature_selection._univariate_selection.GenericUnivariateSelect,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_verbose	false