Xiang Zhang, Yichao Wu, Lan Wang, Runze Li, Variable selection for support vector machines in moderately high dimensions, Journal of the Royal Statistical Society.

For example, sliced inverse regression (Li, 1991) can estimate at most one direction if the response is binary. In this paper we propose principal weighted support vector machines, a unified framework ...

Support Vector Machine (SVM): A supervised learning algorithm that classifies data by finding the hyperplane that best separates different classes, optimising the margin between them.

This paper focuses on feature selection methods for support vector machine (SVM) classifiers, checking their optimality by comparing them with some statistical and baseline methods. To achieve the ...

Support Vector Machines (SVMs) are a versatile and powerful machine learning algorithm that has gained significant popularity for solving classification and regression problems.