Run 10454923

Task 3735 (Supervised Classification) pollen Uploaded 19-05-2020 by Marc Zöller
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sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._factor_analysis.Fac torAnalysis,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	0.7826462085119505
sklearn.tree._classes.DecisionTreeClassifier(3)_class_weight	null
sklearn.tree._classes.DecisionTreeClassifier(3)_criterion	"gini"
sklearn.tree._classes.DecisionTreeClassifier(3)_max_depth	2
sklearn.tree._classes.DecisionTreeClassifier(3)_max_features	0.5194434295667659
sklearn.tree._classes.DecisionTreeClassifier(3)_max_leaf_nodes	2217
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_decrease	0.0934461206012637
sklearn.tree._classes.DecisionTreeClassifier(3)_min_impurity_split	null
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_leaf	0.1979719703194422
sklearn.tree._classes.DecisionTreeClassifier(3)_min_samples_split	0.13530935391260268
sklearn.tree._classes.DecisionTreeClassifier(3)_min_weight_fraction_leaf	0.15901866723631325
sklearn.tree._classes.DecisionTreeClassifier(3)_presort	"deprecated"
sklearn.tree._classes.DecisionTreeClassifier(3)_random_state	42
sklearn.tree._classes.DecisionTreeClassifier(3)_splitter	"best"
sklearn.decomposition._factor_analysis.FactorAnalysis(1)_copy	false
sklearn.decomposition._factor_analysis.FactorAnalysis(1)_iterated_power	3
sklearn.decomposition._factor_analysis.FactorAnalysis(1)_max_iter	8860
sklearn.decomposition._factor_analysis.FactorAnalysis(1)_n_components	3
sklearn.decomposition._factor_analysis.FactorAnalysis(1)_noise_variance_init	null
sklearn.decomposition._factor_analysis.FactorAnalysis(1)_random_state	42
sklearn.decomposition._factor_analysis.FactorAnalysis(1)_svd_method	"lapack"
sklearn.decomposition._factor_analysis.FactorAnalysis(1)_tol	4.156348973047856
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._factor_analysis.FactorAnalysis,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_memory	null
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._factor_analysis.FactorAnalysis,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._factor_analysis.FactorAnalysis,step_1=sklearn.tree._classes.DecisionTreeClassifier)(1)_verbose	false