Missing Values

A data value is missing for a variety of reasonS: it was not measured (that is, has a null value), not answered, was unknown, or was lost. Data mining algorithms vary in the way they treat missing values. There are several typical ways to treat them: ignore then, omit any records containing missing values, replace missing values with the mode or mean, or infer missing values from existing values.

The Missing Values transform allows you to specify how missing values are treated.