A cost-sensitive quantum support vector machine matched classical kernels on minority-class recall in imbalanced employee ...

Support Vector Machines (SVMs) are powerful supervised learning models whose predictive performance depends critically on the choice of hyperparameters, notably the regularisation constant (C) and ...

A support vector machine (SVM) is a type of supervised learning algorithm used in machine learning to solve classification and regression tasks. SVMs aim to find the best possible line, or decision ...

Support vector regression (SVR) predicts a single numeric value using a kernel function, usually RBF, that computes similarity between two data items. SVR makes predictions using support vectors, ...