midSVM
What is Support Vector Regression (SVR)?
Updated May 17, 2026
Short answer
SVR applies SVM principles to regression problems.
Deep explanation
Instead of classification, SVR tries to fit a function within an epsilon margin of tolerance, ignoring small errors and focusing on major deviations.
Real-world example
Used in stock price prediction.
Common mistakes
- Using SVR without feature scaling.
Follow-up questions
- What is epsilon?
- Is SVR sensitive to scaling?