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Discarding Improper Values with Complete Case Analysis
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:doc:`/SingleStepClassifiers/CausalStep/index`

This step deletes all data tuples containing improper values. It is widely used in many statistical packages.

.. rubric:: Input Parameters

1. Input data including improper values

2. Definition of improper values ('nan', 'inf', or 'null', etc.)

.. rubric:: Output Parameters

1. Output data excluding improper values

.. rubric:: Workflow

.. image:: workflow.svg


.. rubric:: References

- G.E.A.P.A. Batista and M.C. Monard, An Analysis of Four Missing Data Treatment Methods for Supervised Learning, Applied Artificial Intelligence, vol. 17(5), pp. 519-533, 2003.

- S.\  Walfish, A review of statistical outlier methods. Pharmaceutical Technology, 2006. Retrieved from www.pharmtech.com.