| Issue | #Downvotes for this reason | By |
|---|
| memory | Used to cache the fitted transformers of the pipeline. The last step will never be cached, even if it is a transformer. By default, no caching is performed. If a string is given, it is the path to the caching directory. Enabling caching triggers a clone of the transformers before fitting. Therefore, the transformer instance given to the pipeline cannot be inspected directly. Use the attribute ``named_steps`` or ``steps`` to inspect estimators within the pipeline. Caching the transformers is advantageous when fitting is time consuming | default: null |
| steps | List of (name of step, estimator) tuples that are to be chained in
sequential order. To be compatible with the scikit-learn API, all steps
must define `fit`. All non-last steps must also define `transform`. See
:ref:`Combining Estimators | default: [{"oml-python:serialized_object": "component_reference", "value": {"key": "pre-processor", "step_name": "pre-processor"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "PDL.Classifier", "step_name": "PDL.Classifier"}}] |
| verbose | If True, the time elapsed while fitting each step will be printed as it is completed. | default: false |