Kernel Machines: Introduction

Kernel machines (or Kernel methods) are crucial approaches in machine learning and have a long and significant history. The core idea is to map input data into a high-dimensional feature space, where it becomes easier to separate classes or fit complex functions. Instead of operating in the high-dimensional space explicitly, which might be computationally prohibitive, we utilize a kernel function to evaluate pairwise similarities between data points. In this chapter, we describe and motivate the core elements of Kernel machines by confining our discussion to the main intuitive, functional aspects and definitions. In this chapter, we describe and motivate the core elements of Kernel machines by confining our discussion to the main intuitive, functional aspects and definitions.