Run 10464223

Task 9983 (Supervised Classification) eeg-eye-state Uploaded 21-05-2020 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.preprocessing._discretization.KBin sDiscretizer,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	0.5698929458178962
sklearn.tree._classes.DecisionTreeClassifier(3)_class_weight	null
sklearn.tree._classes.DecisionTreeClassifier(3)_criterion	"gini"
sklearn.tree._classes.DecisionTreeClassifier(3)_max_depth	54
sklearn.tree._classes.DecisionTreeClassifier(3)_max_features	0.8242424287226779
sklearn.tree._classes.DecisionTreeClassifier(3)_max_leaf_nodes	7032
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_decrease	0.18270993662850915
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_split	null
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_leaf	0.20851605320320418
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_split	0.3820562094050956
sklearn.tree._classes.DecisionTreeClassifier(3)_min_weight_fraction_leaf	0.4710252499809904
sklearn.tree._classes.DecisionTreeClassifier(3)_presort	"deprecated"
sklearn.tree._classes.DecisionTreeClassifier(3)_random_state	42
sklearn.tree._classes.DecisionTreeClassifier(3)_splitter	"best"
sklearn.preprocessing._discretization.KBinsDiscretizer(1)_encode	"onehot"
sklearn.preprocessing._discretization.KBinsDiscretizer(1)_n_bins	24
sklearn.preprocessing._discretization.KBinsDiscretizer(1)_strategy	"uniform"
sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._discretization.KBinsDiscretizer,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_memory	null
sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._discretization.KBinsDiscretizer,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._discretization.KBinsDiscretizer,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_verbose	false