In this work, we developed classifiers to distinguish between four ovarian tumor types using Bayesian least squares support vector machines (LS-SVMs) and kernel logistic regression...
Ben Van Calster, Dirk Timmerman, Antonia C. Testa,...
In this paper, a multi-class feature selection scheme based on recursive feature elimination (RFE) is proposed for texture classifications. The feature selection scheme is perform...
A new method for classification is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by a ...
Abstract. Motivation: Although studies have shown that genetic alterations are causally involved in numerous human diseases, still not much is known about the molecular mechanisms ...
Anneleen Daemen, Olivier Gevaert, Karin Leunen, Va...
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...