This paper investigates the use of a one-class support vector machine algorithm to detect the onset of system anomalies, and trend output classification probabilities, as a way to ...
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,...
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
In this paper we address two aspects related to the exploitation of Support Vector Machines (SVM) for classification in real application domains, such as the detection of objects ...
– In this paper we perform a t-test for significant gene expression analysis in different dimensions based on molecular profiles from microarray data, and compare several computa...
Krishna Yendrapalli, Ram B. Basnet, Srinivas Mukka...