Abstract. In this paper we discuss sparse least squares support vector regressors (sparse LS SVRs) defined in the reduced empirical feature space, which is a subspace of mapped tr...
Abstract— Support vector machines are very accurate classifiers and have been widely used in many applications. However, the training and to a lesser extent prediction time of s...
Tong Luo, Lawrence O. Hall, Dmitry B. Goldgof, And...
In this paper we propose a modified framework of support vector machines, called Oblique Support Vector Machines(OSVMs), to improve the capability of classification. The principl...
We present and discuss several spatiotemporal kernels designed to mine real-life and simulated data in support of drought prediction. We implement and empirically validate these k...
In this poster we present an overview of the techniques we used to develop and evaluate a text categorisation system for the PRINCIP project which sets out to automatically classi...