Visualisation of High-Dimensional Data for Very Large Data Sets
David C. M. Wong, Iain Strachan, Lionel Tarassenko · 2008
This paper proposes a modification on the Sammon map algorithm for data visualisation. The modification, known as the Sparse Approximated Sammon Stress(SASS), allows mappings to be produced for very large data sets of the order of 10 6 points. While the technique may be useful in a variety of applications, the results presented here will demonstrate its usefulness for visualising patient deterioration in vital sign data collected from step-down unit hospital patients. A final result demonstrates an application of the SASS visualisation for drug safety analysis.