Supervised dimensionality reduction for big data

Abstract

Biomedical measurements usually generate high-dimensional data where individual samples are classified in several categories. Vogelstein et al. propose a supervised dimensionality reduction method which estimates the low-dimensional data projection for classification and prediction in big datasets.