.. _auto_dataset_remove_outliers:

*DATASET REMOVE OUTLIERS*
=========================

Detects and removes outlier rows from a dataset using iterative statistical analysis on one or more specified columns. Use this worker to clean noisy tabular data before model training, statistical analysis, or reporting.

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

Classification: **process**.

Tagged: ``data_cleaning``, ``iterative``, ``outlier_removal``, ``row_filter``, ``statistics``.

Inputs
------

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   :header-rows: 1
   :widths: 20 20 20 20 20 20

   * - Label
     - ID
     - Type
     - Default
     - Required
     - Description
   * - Dataset
     - dataset
     - dataset
     - —
     - 
     - Tabular dataset to be scanned for outliers; all rows in this dataset are candidates for removal if outlying values are detected in the specified columns.
   * - Columns To Check
     - columnstocheck
     - scalar
     - —
     - 
     - One or more column names (comma-separated or multi-select) from the input dataset whose values will be evaluated for outliers; leave unset to check all numeric columns.
   * - Number Of Iterations
     - num_iterations
     - scalar
     - 1
     - 
     - Number of successive outlier-removal passes to perform (integer ≥ 1); default is 1 — increase when iterative removal is needed to handle clusters of extreme values.

Outputs
-------

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

   * - Label
     - ID
     - Type
     - Description
   * - dataset_remove_outliers_output_1
     - dataset_remove_outliers_output_1
     - dataset
     - Cleaned dataset with outlier rows removed, retaining the same column schema as the input dataset.

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

- data.dataset.transform
- data.statistics

Runnable example
----------------

A runnable example is registered for this worker. Open the example workflow on the d3VIEW canvas: `/api/workflow/example?id=dataset_remove_outliers <https://www.d3view.com/api/workflow/example?id=dataset_remove_outliers>`_

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   Auto-generated from <code>transformation</code> schema. Worker id: <code>dataset_remove_outliers</code>. Schema hash: <code>1b2913a53bd9</code>. Hand-curated docs in <code>workerexamples/</code> override this page when present.
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