Using data images for outlier detection

Authors:
David J. Marchette;Jeffrey L. Solka
Affiliations:
Naval Surface Warfare Center, Code B10, 17320 Dahlgren Road, Dahlgren, VA;Naval Surface Warfare Center, Code B10, 17320 Dahlgren Road, Dahlgren, VA
Venue:
Computational Statistics & Data Analysis - Data visualization
Year:
2003

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Abstract

The data image has been proposed as a method for visualizing high-dimensional data. The idea is to map the data into an image, by using gray-scale (or color) values to indicate the magnitude of each variate. Thus, the image for a data set of size n and dimension d is a d × η image, where the columns correspond to observations and the rows to variates. We consider the application of this idea to the detection of outliers, providing a simple visualization technique that highlights outliers and clusters within the data.