SVM Theory: Margins and Support Vectors
Maximum margin classifier, hard vs soft margin (C parameter), support vectors.
What Is an SVM
A Support Vector Machine is a classifier that finds the boundary best separating two classes. Instead of any separating line, it seeks the one with the widest gap between classes.
The Separating Hyperplane
In 2D the boundary is a line; in higher dimensions it is a hyperplane. The SVM defines it as w . x + b = 0, classifying points by which side they fall on.
All lessons in this course
- SVM Theory: Margins and Support Vectors
- Kernel Trick: RBF, Polynomial, and Sigmoid
- SVMs for Classification with sklearn
- SVMs for Regression (SVR)