AI engineering glossary · Classical ML algorithms
What is SVR (support vector regression)?
Support vector regression (also called SVR): An adaptation of margin-based learning to predict numbers. It fits a function that stays within a tolerance band epsilon of the targets, ignoring small errors and penalising only points outside the band.
Support vector regression: an example
SVR(epsilon=2.0) predicting temperature treats errors under 2 degrees as costless.
Related terms
More Classical ML algorithms terms
Where you learn it
Support vector regression is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.