Run 2011

Task 119 (Supervised Classification) diabetes Uploaded 12-01-2024 by Continuous Integration
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads

Issue	#Downvotes for this reason	By

Flow

TEST1ee00ff1cbsklearn.pipeline.Pipeline(imputer=sklearn.impute._base.Simple Imputer,classifier=sklearn.dummy.DummyClassifier)(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``.
TEST1ee00ff1cbsklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.dummy.DummyClassifier)(1)_memory	null
TEST1ee00ff1cbsklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.dummy.DummyClassifier)(1)_steps	[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "classifier", "step_name": "classifier"}}]
TEST1ee00ff1cbsklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,classifier=sklearn.dummy.DummyClassifier)(1)_verbose	false
TEST1ee00ff1cbsklearn.impute._base.SimpleImputer(1)_add_indicator	false
TEST1ee00ff1cbsklearn.impute._base.SimpleImputer(1)_copy	true
TEST1ee00ff1cbsklearn.impute._base.SimpleImputer(1)_fill_value	null
TEST1ee00ff1cbsklearn.impute._base.SimpleImputer(1)_missing_values	NaN
TEST1ee00ff1cbsklearn.impute._base.SimpleImputer(1)_strategy	"mean"
TEST1ee00ff1cbsklearn.impute._base.SimpleImputer(1)_verbose	0
TEST1ee00ff1cbsklearn.dummy.DummyClassifier(1)_constant	null
TEST1ee00ff1cbsklearn.dummy.DummyClassifier(1)_random_state	45101
TEST1ee00ff1cbsklearn.dummy.DummyClassifier(1)_strategy	"prior"