Feature Extraction of High-Dimensional Structures for Exploratory Analytics

Report No. ARL-TN-531
Authors: Andrew M. Neiderer
Date/Pages: April 2013; 14 pages
Abstract: This report summarizes lessons learned in a study conducted at the U.S. Army Research Laboratory (ARL) for visual examination of high-dimensional data (HDD). The initial effort included feature extraction (FE), as opposed to feature selection, of HDD structures for display. FE to a two- or three-dimensional Euclidean space allows exploration of underlying structure of HDD, even though the meaning of the actual data is obscured (latent variables). Some discussion of the FEs considered is given; further details can be found at URLs provided. Application of visual analytics technology (interaction/navigation within visualization) allows additional knowledge discovery. Research continues at ARL for the development of a method to gain insight into HDD, particularly in the application of an analytic strategy to terrorist data.
Distribution: Approved for public release
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Last Update / Reviewed: April 1, 2013