Improve Data Quality (automated data preparation)
Prepare fields to improve data quality. Deselecting this option disables all other Improve Data Quality controls while maintaining the selections.
Outlier Handling. Specify whether to replace outliers for the inputs and target; if so, specify an outlier cutoff criterion, measured in standard deviations, and a method for replacing outliers. Outliers can be replaced by either trimming (setting to the cutoff value), or by setting them as missing values. Any outliers set to missing values follow the missing value handling settings selected below.
Replace Missing Values. Specify whether to replace missing values of continuous, nominal, or ordinal fields.
Reorder Nominal Fields. Select this to recode the values of nominal (set) fields from smallest (least frequently occurring) to largest (most frequently occurring) category. The new field values start with 0 as the least frequent category. Note that the new field will be numeric even if the original field is a string. For example, if a nominal field's data values are "A", "A", "A", "B", "C", "C", then automated data preparation would recode "B" into 0, "C" into 1, and "A" into 2.