Run 10456766

Task 3797 (Supervised Classification) socmob Uploaded 19-05-2020 by Marc Zöller
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sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.on e_hot_encoding.OneHotEncoderComponent,step_1=sklearn.decomposition._kernel_ pca.KernelPCA,step_2=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	0.7501233589949263
sklearn.tree._classes.DecisionTreeClassifier(3)_class_weight	null
sklearn.tree._classes.DecisionTreeClassifier(3)_criterion	"entropy"
sklearn.tree._classes.DecisionTreeClassifier(3)_max_depth	29
sklearn.tree._classes.DecisionTreeClassifier(3)_max_features	0.558496686944906
sklearn.tree._classes.DecisionTreeClassifier(3)_max_leaf_nodes	971
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_decrease	0.4116864170276987
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_split	null
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_leaf	0.35442863980855444
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_split	0.27129109134123647
sklearn.tree._classes.DecisionTreeClassifier(3)_min_weight_fraction_leaf	0.0636968707586319
sklearn.tree._classes.DecisionTreeClassifier(3)_presort	"deprecated"
sklearn.tree._classes.DecisionTreeClassifier(3)_random_state	42
sklearn.tree._classes.DecisionTreeClassifier(3)_splitter	"best"
sklearn.decomposition._kernel_pca.KernelPCA(1)_alpha	1.0
sklearn.decomposition._kernel_pca.KernelPCA(1)_coef0	1
sklearn.decomposition._kernel_pca.KernelPCA(1)_copy_X	false
sklearn.decomposition._kernel_pca.KernelPCA(1)_degree	3
sklearn.decomposition._kernel_pca.KernelPCA(1)_eigen_solver	"dense"
sklearn.decomposition._kernel_pca.KernelPCA(1)_fit_inverse_transform	false
sklearn.decomposition._kernel_pca.KernelPCA(1)_gamma	1.569281682936436e-08
sklearn.decomposition._kernel_pca.KernelPCA(1)_kernel	"rbf"
sklearn.decomposition._kernel_pca.KernelPCA(1)_kernel_params	null
sklearn.decomposition._kernel_pca.KernelPCA(1)_max_iter	285
sklearn.decomposition._kernel_pca.KernelPCA(1)_n_components	33
sklearn.decomposition._kernel_pca.KernelPCA(1)_n_jobs	1
sklearn.decomposition._kernel_pca.KernelPCA(1)_random_state	42
sklearn.decomposition._kernel_pca.KernelPCA(1)_remove_zero_eig	true
sklearn.decomposition._kernel_pca.KernelPCA(1)_tol	0
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.one_hot_encoding.OneHotEncoderComponent,step_1=sklearn.decomposition._kernel_pca.KernelPCA,step_2=sklearn.tree._classes.DecisionTreeClassifier)(1)_memory	null
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.one_hot_encoding.OneHotEncoderComponent,step_1=sklearn.decomposition._kernel_pca.KernelPCA,step_2=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"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "step_2", "step_name": "step_2"}}]
sklearn.pipeline.Pipeline(step_0=automl.components.feature_preprocessing.one_hot_encoding.OneHotEncoderComponent,step_1=sklearn.decomposition._kernel_pca.KernelPCA,step_2=sklearn.tree._classes.DecisionTreeClassifier)(1)_verbose	false