This paper studies the training of support vector machine (SVM) classifiers with respect to the minimax and Neyman-Pearson criteria. In principle, these criteria can be optimized in a straightforward way using a cost-sensitive SVM. In practice, however, because these criteria require especially...

In recent years, evidence has emerged indicating that magnetic resonance imaging (MRI) brain scans provide valuable diagnostic information about Alzheimer’s disease. It has been shown that MRI brain scans are capable of both diagnosing Alzheimer’s disease itself at an early stage and...

The problem of regression shrinkage and selection for multivariate regression is considered. The goal is to consistently identify those variables relevant for regression. This is done not only for predictors but also for responses. To this end, a novel relationship between multivariate...

Providing accurate wind speed prediction algorithms has become increasingly significant because of the important technological and economic impacts of wind speed on wind power generation. In this study, two combined strategies for wind speed forecasting are proposed and followed. Four approaches...

A clustering approach is presented for short-term prediction of power produced by a wind turbine at low wind speeds. Increased prediction accuracy of wind power to be produced at future time periods is often bounded by the prediction model complexity and computational time involved. In this...