Derived Feature

Derived features refer to the practice of creating new, more informative variables from existing fields. Examples include converting age into age groups, turning timestamps into weekday/weekend indicators, or computing total spend from price and quantity. Such features can help the model detect patterns that are not explicit in the raw data. Strong feature engineering often comes not from adding more data, but from making the existing data more meaningful. Derived features are therefore one of the most effective ways of injecting domain knowledge into a model.