AI engineering glossary · ML fundamentals
What is feature space?
Feature space (also called Input space): The abstract space in which each example is a point and each feature is one axis. With 3 features data lives in 3-D space; with 300 it lives in 300 dimensions. Many algorithms are described as geometric operations in it, such as distances or separating surfaces.
Feature space: an example
A customer with age 30, income 8 lakh and 4 orders is the point (30, 8, 4) in a three-dimensional space.
Related terms
More ML fundamentals terms
- Generalisation
- Generalisation error
- Generalisation gap
- Generative model
- Grid search
- Ground truth
- Group k-fold
- Holdout method
Where you learn it
Feature space is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.