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Random Graphs for Statistical Pattern Recognition



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Random Graphs for Statistical Pattern Recognition by David Marchette
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Random Graphs for Statistical Pattern Recognition describes several classes of random graphs used in pattern recognition. It covers the neighborhood graphs introduced by Toussaint, as well as the various generalizations and specific cases. These graphs have been widely used for clustering. A newly introduced random graph, called the class cover catch digraph (CCD), is the primary focus of the book. The properties of the CCCD are investigated, along with applications to discrimination, dimensionality reduction, and aggregation/association detection.

Author Biography

DAVID J. MARCHETTE, PhD, is a researcher at the Naval Surface Warfare Center in Dahlgren, Virginia, where he investigates computational statistics and pattern recognition, primarily as it applies to image processing, automatic target recognition, and computer security. He is also an adjunct professor at George Mason University and a lecturer at Johns Hopkins University.
Release date NZ
February 23rd, 2004
Country of Publication
United States
John Wiley & Sons Inc
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