| 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": "num", "step_name": "num", "argument_1": ["duration", "credit_amount", "installment_commitment", "residence_since", "age", "existing_credits", "num_dependents"]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": ["checking_status", "credit_history", "purpose", "savings_status", "employment", "personal_status", "other_parties", "property_magnitude", "other_payment_plans", "housing", "job", "own_telephone", "foreign_worker"]}}] |
| verbose | If True, the time elapsed while fitting each transformer will be printed as it is completed. | default: false |