Run 10459449

Task 9981 (Supervised Classification) cnae-9 Uploaded 20-05-2020 by Marc Zöller
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sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._pca.PCA,step_1=skle arn.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	0.09431921868286319
sklearn.tree._classes.DecisionTreeClassifier(3)_class_weight	null
sklearn.tree._classes.DecisionTreeClassifier(3)_criterion	"entropy"
sklearn.tree._classes.DecisionTreeClassifier(3)_max_depth	105
sklearn.tree._classes.DecisionTreeClassifier(3)_max_features	0.45636427866278956
sklearn.tree._classes.DecisionTreeClassifier(3)_max_leaf_nodes	675
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_decrease	0.1214807717340558
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_split	null
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_leaf	0.48504348498079014
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_split	0.21530090929813034
sklearn.tree._classes.DecisionTreeClassifier(3)_min_weight_fraction_leaf	0.38993981944391265
sklearn.tree._classes.DecisionTreeClassifier(3)_presort	"deprecated"
sklearn.tree._classes.DecisionTreeClassifier(3)_random_state	42
sklearn.tree._classes.DecisionTreeClassifier(3)_splitter	"best"
sklearn.decomposition._pca.PCA(1)_copy	false
sklearn.decomposition._pca.PCA(1)_iterated_power	52
sklearn.decomposition._pca.PCA(1)_n_components	111
sklearn.decomposition._pca.PCA(1)_random_state	42
sklearn.decomposition._pca.PCA(1)_svd_solver	"randomized"
sklearn.decomposition._pca.PCA(1)_tol	3.9097780818058077
sklearn.decomposition._pca.PCA(1)_whiten	false
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._pca.PCA,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_memory	null
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._pca.PCA,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._pca.PCA,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_verbose	false