For general information about outliers, see Outliers in Oracle Data Mining.
You can change the definition of "outlier" by changing the number of standard deviations or by entering an explicit cutoff point, either as a percentage of records or as an actual value. You can also choose to discard extreme values rather than to recode them.
To define an outlier treatment, you must supply two pieces of information:
AVG-3*Sigma
or values > AVG+3*Sigma
are outliers. You can also specify the percent of values in each tail or upper and lower values.NULL
values (that is, discard outliers) 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 the edge value -5.Click OK to continue.
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