juniorSVM
What is a Support Vector Machine (SVM)?
Updated May 17, 2026
Short answer
SVM is a supervised ML algorithm used for classification and regression that finds the optimal hyperplane separating classes.
Deep explanation
Support Vector Machine works by finding a decision boundary (hyperplane) that maximizes the margin between different classes. The key idea is that better separation leads to better generalization. It relies on support vectors, which are the critical data points closest to the decision boundary.
Real-world example
Used in email spam detection to classify emails as spam or not spam.
Common mistakes
- Thinking SVM only works for linear data or confusing it with clustering algorithms.
Follow-up questions
- What are support vectors?
- Is SVM supervised or unsupervised?