.. _fwflag_fold_column:
==============
--fold_column
==============
Switch
======

--fold_column FIELD

Description
===========

A column in :doc:`fwflag_outcome_table` giving pre-assigned fold labels to use for cross-validation in prediction/classification, instead of DLATK randomly splitting groups into folds.

Argument and Default Value
==========================

A column name. Default: ``None`` (random folds). Aliased as ``--fold_labels``.

Details
=======

Passed straight through to ``OutcomeGetter(..., fold_column=args.fold_column)``, so every group's fold membership comes from this column's value rather than a random assignment — useful for reproducible splits, or splits that must respect a grouping (e.g. no user split across folds if pre-aggregated by some other unit). Use :doc:`fwflag_test_folds` to restrict evaluation to a subset of the fold values found in this column.

Other Switches
==============

Required Switches:

* One of :doc:`fwflag_combo_test_regression`, :doc:`fwflag_combo_test_classifiers`, or another cross-validated prediction switch

Optional Switches:

* :doc:`fwflag_test_folds`

Example Commands
================

.. code-block:: bash

	dlatkInterface.py -d dla_tutorial -t msgs -c user_id -f 'feat$1gram$msgs$user_id$16to16' \
	--outcome_table blog_outcomes --outcomes age --fold_column predefined_fold --combo_test_regression