On the Selection of Dimension Reduction Techniques for Scientific Applications

Abstract

Abstract Many dimension reduction methods have been proposed to discover the intrinsic, lower dimensional structure of a high-dimensional dataset. However, determining critical features in datasets that consist of a large number of features is still a challenge. In this article, through a series of carefully designed experiments on real-world datasets, we investigate the performance of different dimension reduction techniques, ranging from ...