AI engineering glossary · Classical ML algorithms
What is euclidean distance?
Euclidean distance: The straight-line distance between two points: the square root of the sum of squared differences in each coordinate. It is the default similarity measure in neighbour and clustering methods and is sensitive to feature scale.
Euclidean distance: an example
Between (1, 2) and (4, 6) the distance is sqrt(3^2 + 4^2) = 5.
Related terms
More Classical ML algorithms terms
- Expectation-maximisation
- Explained variance ratio
- Extremely randomised trees
- Feature importance
- Gaussian mixture model
- Gaussian naive Bayes
- Gaussian process
- Gini impurity
Where you learn it
Euclidean distance is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.