Discarding Improper Values with Complete Case AnalysisΒΆ

Causal Step

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

Input Parameters

  1. Input data including improper values
  2. Definition of improper values (‘nan’, ‘inf’, or ‘null’, etc.)

Output Parameters

  1. Output data excluding improper values

Workflow

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