.. _auto_dataset_normalize_apply:

*DATASET NORMALIZE (APPLY)*
===========================

Applies a previously-fitted normalization (mean/std parameters from dataset_normalize_fit) to a new dataset WITHOUT refitting -- the train/test discipline. Skips id/mid/*_id columns; columns with no saved parameters are left unchanged; missing cells are left as-is; std==0 is treated as 1.0.

When to use
-----------

Tagged: ``normalization``, ``standardize``, ``zscore``, ``scaling``, ``apply``, ``transform``, ``train_test``, ``preprocessing``.

Inputs
------

.. list-table::
   :header-rows: 1
   :widths: 20 20 20 20 20 20

   * - Label
     - ID
     - Type
     - Default
     - Required
     - Description
   * - Dataset
     - dataset
     - dataset
     - —
     - ✓
     - Testing/new dataset to normalize with the saved parameters; array-of-row-objects.
   * - Normalization Parameters
     - parameters
     - dataset
     - —
     - ✓
     - Parameters dataset produced by dataset_normalize_fit; rows of {column, mean, std}.

Outputs
-------

.. list-table::
   :header-rows: 1
   :widths: 20 20 20 20

   * - Label
     - ID
     - Type
     - Description
   * - Normalized Dataset
     - dataset
     - dataset
     - Input dataset normalized using the supplied saved parameters.
   * - Status
     - status
     - string
     - Summary of how many columns were transformed vs left unchanged.

Disciplines
-----------

- data.dataset.transform
- data.statistics

.. raw:: html

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   Auto-generated from <code>platform</code> schema. Worker id: <code>dataset_normalize_apply</code>. Schema hash: <code>8c5513df78c8</code>. Hand-curated docs in <code>workerexamples/</code> override this page when present.
   </p>