1.1 - 8.10 - OutlierFilter (ML Engine) - Teradata Vantage

Teradata Vantage™ - Machine Learning Engine Analytic Function Reference

Teradata Vantage
Release Number
October 2019
Content Type
Programming Reference
Publication ID
English (United States)

The OutlierFilter function is useful for filtering a numeric data set before applying ML Engine functions for which outliers can skew the estimates of parameters and cause inaccurate predictions. Such functions include time series functions, GLM, LAR, LinReg, PCA, and KMeans. The input data set is expected to have millions of attribute-value pairs.

The OutlierFilter function filters outliers from a data set, either deleting them or replacing them with a specified value. Optionally, the function stores the outliers in their own table. The function provides these methods for filtering outliers:
  • Percentile
  • Tukey's test
  • Carling's modification to Tukey's test
  • Median absolute deviation

The method determines the criteria for an observation to classify as an outlier.