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Find missing values and replace them with appropriate values. This transformation replaces missing values with an appropriate value.
To specify a missing values transformation, set Transform Type to Missing Values and specify how to replace missing values.
These are the following possibilities for replacement:
Statistic: replace missing value with a statistical measure. Statistic is the default treatment for missing values.
The possible statistics depend on the data type of the column:
For numerical columns, you can replace missing values with mean (the default), minimum, maximum, and median.
For categorical columns, you can replace missing values with the mode (the default).
Value: Replace missing values with the specified value. Data Miner provides a default value which you can change. If statistics are not available, the default value is 0. If statistics are available, the default value is the mean for numerical columns and the mode for categorical columns.
Both of these treatments can be applied to attributes that have a date or time data type (DATE, TIMESTAMP, TIMESTAMP_WITH_LOCAL_ TIMEZONE, and TIMESTAMP_WITH_TIMEZONE).