AI engineering glossary · Feature engineering data prep
What is missing indicator?
Missing indicator (also called Missingness flag): An extra binary column marking whether a value was missing in the original row. It lets a model learn from the fact of missingness itself, which is often informative, while the original column is imputed.
Missing indicator: an example
If applicants who leave 'income' blank default more often, an income_missing flag lets the model exploit this.
Related terms
More Feature engineering data prep terms
- Missing not at random
- Missing value imputation
- Mode imputation
- Multiple imputation
- Mutual information
- Nominal variable
- One-hot encoding
- Ordinal encoding
Where you learn it
Missing indicator is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.