Intermediate · Fundamentals
Feature cross
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. A feature cross combines two or more categorical features to create a new synthetic feature, capturing interaction effects.
Technical Definition
A feature cross combines two or more categorical features to create a new synthetic feature, capturing interaction effects.
How it works
A feature cross is a technique used in machine learning to explicitly model the interaction between two or more categorical or bucketed numerical features. It creates a new feature that represents all possible combinations of the original features. This allows a linear model to learn non-linear relationships that might otherwise be missed.
Related Concepts
- Feature Engineering — The process of creating, selecting, and transforming input variables to improve a machine learning model's performance.
- Categorical data — Data that represents categories or labels, where each data point belongs to one specific group from a defined set of possibilities.