The RBF kernel allows computations of dot products in high-dimensional spaces without explicitly visiting those spaces, making it powerful for modeling complex decision boundaries. It's the default kernel in sklearn's support vector classifier and demonstrates how high-dimensional operations are performed with reduced computational complexity.
Table of contents
Before I begin, here’s a note for DS/ML/AI companies reading this newsletterThe math behind RBF kernelAre you overwhelmed with the amount of information in ML/DS?Sort: