Outlier Treatment Options

For general information about outliers, see Outliers in Oracle Data Mining.

To define an outlier treatment, you must supply two pieces of information:

  1. Cutoff Points: Specify the values that are outliers (for example, values that are more than 3 standard deviations from the mean).
  2. Replace with: Specify how to treat the outliers. You can either replace the values with NULL values (that is, throw the values away) or you can replace then with edge values. Suppose that 10 is the mean of an attribute's distribution and 5 is the standard deviation. Suppose that outliers are values that are less than -5 (the mean minus 3 times the standard deviation) or greater than 25 (the mean plus three times the standard deviation), then you can either replace the value -10 with NULL or replace it with -5.