| Issue | #Downvotes for this reason | By |
|---|
| n_jobs | Number of jobs to run in parallel
``None`` means 1 unless in a :obj:`joblib.parallel_backend` context
``-1`` means using all processors. See :term:`Glossary | default: null |
| remainder | default: "drop" | |
| sparse_threshold | If the output of the different transformers contains sparse matrices, these will be stacked as a sparse matrix if the overall density is lower than this value. Use ``sparse_threshold=0`` to always return dense. When the transformed output consists of all dense data, the stacked result will be dense, and this keyword will be ignored | default: 0.3 |
| transformer_weights | Multiplicative weights for features per transformer. The output of the transformer is multiplied by these weights. Keys are transformer names, values the weights | default: null |
| transformers | List of (name, transformer, columns) tuples specifying the transformer objects to be applied to subsets of the data | default: [{"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [0, 3, 4, 5, 6, 8, 9, 11, 12]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cont", "step_name": "cont", "argument_1": [1, 2, 7, 10, 13, 14]}}] |
| verbose | If True, the time elapsed while fitting each transformer will be printed as it is completed. | default: false |