David Bremner, Erik Demaine, Jeff Erickson, John Iacono, Stefan Langerman, Pat Morin, Godfried Toussaint  Home/Search
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Abstract: Given a set R of red points and a set B of blue points, the nearest-neighbour decision rule classifies a new point q as red (respectively, blue) if the closest point to q in R ∪ B comes from R (respectively, B). This rule implicitly partitions space into a red set and a blue set that are separated by a red-blue decision boundary. In this paper we develop output-sensitive algorithms for computing this decision boundary for point sets on the line and in R². Both algorithms run in time... (Update)
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BibTeX entry: (Update)
@misc{ bremner-outputsensitive,
author = "David Bremner and Erik Demaine and Jeff Erickson and John Iacono and Stefan
Langerman and Pat Morin and Godfried Toussaint",
title = "Output-Sensitive Algorithms for Computing Nearest-Neighbour Decision Boundaries",
url = "citeseer.ist.psu.edu/695764.html" }
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