Flow
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))

sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))

Visibility: public Uploaded 15-03-2019 by Rafael M. O. Cruz sklearn==0.20.3 numpy>=1.6.1 scipy>=0.9 0 runs
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
  • openml-python python scikit-learn sklearn sklearn_0.20.3
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Automatically created scikit-learn flow.

Parameters

n_jobsdefault: null
remainderdefault: "passthrough"
sparse_thresholddefault: 0.3
transformer_weightsdefault: null
transformersdefault: [{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": []}}]

0
Runs

List all runs
Parameter:
Rendering chart
Rendering table