XOR

Nonlinear SVM

May 28, 2026
Mathematical Foundations for Machine Learning
MFML, SVM, Nonlinear SVM, Kernel Trick, Kernel Functions, XOR

Nonlinear SVM #

A linear SVM works well when the data can be separated by a straight line or hyperplane. When the data is not linearly separable in the original input space, nonlinear SVM maps the data to a higher-dimensional feature space where a linear separator may exist.

Key takeaway: Nonlinear SVM uses the kernel trick. Instead of explicitly mapping

\( x \)

to ( \phi(x) )