Kernel methods and support vector machines (SVMs) serve as cornerstones in modern machine learning, offering robust techniques for both classification and regression tasks. At their core, kernel ...

The goal of a machine learning regression problem is to predict a single numeric value, for example, predicting a person's income based on their age, height, years of education, and so on. There are ...

In this paper, we propose a kernel-free semi-supervised quadratic surface support vector machine model for binary classification. The model is formulated as a mixed-integer programming problem, which ...

Kernel methods are a class of machine learning algorithms which learn and discover patterns in a high (possibly infinite) dimensional feature space obtained by often nonlinear, possibly infinite ...