Run 10593679

Task 361444 (Supervised Classification) phoneme Uploaded 09-05-2023 by Takeaki Sakabe
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads

Issue	#Downvotes for this reason	By

Flow

sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estima tor=sklearn.semi_supervised._label_propagation.LabelPropagation)(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.impute._base.SimpleImputer(43)_add_indicator	false
sklearn.impute._base.SimpleImputer(43)_copy	true
sklearn.impute._base.SimpleImputer(43)_fill_value	null
sklearn.impute._base.SimpleImputer(43)_keep_empty_features	false
sklearn.impute._base.SimpleImputer(43)_missing_values	NaN
sklearn.impute._base.SimpleImputer(43)_strategy	"mean"
sklearn.impute._base.SimpleImputer(43)_verbose	"deprecated"
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.semi_supervised._label_propagation.LabelPropagation)(1)_memory	null
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.semi_supervised._label_propagation.LabelPropagation)(1)_steps	[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": "estimator"}}]
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.semi_supervised._label_propagation.LabelPropagation)(1)_verbose	false
sklearn.semi_supervised._label_propagation.LabelPropagation(1)_gamma	20
sklearn.semi_supervised._label_propagation.LabelPropagation(1)_kernel	"rbf"
sklearn.semi_supervised._label_propagation.LabelPropagation(1)_max_iter	1000
sklearn.semi_supervised._label_propagation.LabelPropagation(1)_n_jobs	null
sklearn.semi_supervised._label_propagation.LabelPropagation(1)_n_neighbors	7
sklearn.semi_supervised._label_propagation.LabelPropagation(1)_tol	0.001