This paper describes a novel application of support vector machines and multiscale texture and color invariants to a problem in biological oceanography: the identification of 6 sp...
Background: Understanding how amino acid substitutions affect protein functions is critical for the study of proteins and their implications in diseases. Although methods have bee...
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,...
Abstract. Protein membership prediction is a fundamental task to retrieve information for unknown or unidentified sequences. When support vector machines (SVMs) are associated with...
We present a new method for transductive learning, which can be seen as a transductive version of the k nearest-neighbor classifier. Unlike for many other transductive learning me...