Data Science & ML

Feature Engineering

/ˈfiːtʃər ˌendʒɪˈnɪərɪŋ/

Definition

The process of transforming raw data into informative input features that improve model performance.

Example in context

"Extracting day-of-week from a timestamp was the key feature — the model's AUC jumped from 0.71 to 0.85."

Related terms

Practice this term

Master Feature Engineering in context by working through exercises in the Data Science & ML module. You'll see the term used in real engineering scenarios with multiple-choice, fill-in-the-blank, and matching drills.

Frequently Asked Questions

What does "Feature Engineering" mean?

The process of transforming raw data into informative input features that improve model performance.

How do you pronounce "Feature Engineering"?

"Feature Engineering" is pronounced /ˈfiːtʃər ˌendʒɪˈnɪərɪŋ/.

Can you use "Feature Engineering" in a sentence?

"Extracting day-of-week from a timestamp was the key feature — the model's AUC jumped from 0.71 to 0.85."