Cross-validated feature selection using least-squares support vector machines for binary classification

Support vector machines (SVMs) are widely used for binary classification. However, irrelevant or redundant features can degrade classification accuracy and model interpretability, making feature selection important for SVMs. Most SVM feature selection methods rely on sequential search or regularizat