Run 10459164

Task 9981 (Supervised Classification) cnae-9 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.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	0.6900857821032496
sklearn.tree._classes.DecisionTreeClassifier(3)_class_weight	null
sklearn.tree._classes.DecisionTreeClassifier(3)_criterion	"entropy"
sklearn.tree._classes.DecisionTreeClassifier(3)_max_depth	42
sklearn.tree._classes.DecisionTreeClassifier(3)_max_features	0.06574162794305957
sklearn.tree._classes.DecisionTreeClassifier(3)_max_leaf_nodes	759
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_decrease	0.1938140221394432
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_split	null
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_leaf	0.30306510944037895
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_split	0.09192149599845495
sklearn.tree._classes.DecisionTreeClassifier(3)_min_weight_fraction_leaf	0.4384331913754587
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	53
sklearn.decomposition._fastica.FastICA(1)_n_components	124
sklearn.decomposition._fastica.FastICA(1)_random_state	42
sklearn.decomposition._fastica.FastICA(1)_tol	0.8637531611802648
sklearn.decomposition._fastica.FastICA(1)_w_init	null
sklearn.decomposition._fastica.FastICA(1)_whiten	true
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