Run 10464495

Task 9983 (Supervised Classification) eeg-eye-state Uploaded 22-05-2020 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.decomposition._truncated_svd.Trunc atedSVD,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	0.8313123533424543
sklearn.tree._classes.DecisionTreeClassifier(3)_class_weight	null
sklearn.tree._classes.DecisionTreeClassifier(3)_criterion	"entropy"
sklearn.tree._classes.DecisionTreeClassifier(3)_max_depth	5
sklearn.tree._classes.DecisionTreeClassifier(3)_max_features	0.2748670764314364
sklearn.tree._classes.DecisionTreeClassifier(3)_max_leaf_nodes	13329
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_decrease	0.07999090530465885
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_split	null
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_leaf	0.36850252579369863
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_split	0.2834906943001634
sklearn.tree._classes.DecisionTreeClassifier(3)_min_weight_fraction_leaf	0.10667426241679101
sklearn.tree._classes.DecisionTreeClassifier(3)_presort	"deprecated"
sklearn.tree._classes.DecisionTreeClassifier(3)_random_state	42
sklearn.tree._classes.DecisionTreeClassifier(3)_splitter	"random"
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._truncated_svd.TruncatedSVD,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_memory	null
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._truncated_svd.TruncatedSVD,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._truncated_svd.TruncatedSVD,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_verbose	false
sklearn.decomposition._truncated_svd.TruncatedSVD(1)_algorithm	"arpack"
sklearn.decomposition._truncated_svd.TruncatedSVD(1)_n_components	9
sklearn.decomposition._truncated_svd.TruncatedSVD(1)_n_iter	22
sklearn.decomposition._truncated_svd.TruncatedSVD(1)_random_state	42
sklearn.decomposition._truncated_svd.TruncatedSVD(1)_tol	1.7075144408064993