Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/42858
Title: Efficient computation of voronoi neighbors based on polytope search in pattern recognition
Authors: Mendez, Juan 
Lorenzo, Javier 
UNESCO Clasification: 120304 Inteligencia artificial
Keywords: Pattern Recognition
Machine Learning
Nearest Neighbors
Voronoi adjacency
Linear programming
Issue Date: 2012
Conference: 1st International Conference on Pattern Recognition Applications and Methods, ICPRAM 2012 
Abstract: Some algorithms in Pattern Recognition and Machine Learning as neighborhood-based classification and dataset condensation can be improved with the use of Voronoi tessellation. The paper shows the weakness of some existing algorithms of tessellation to deal with high dimensional datasets. The use of linear programming can improve the tessellation procedures by focusing in Voronoi adjacency. It will be shown that the adjacency test based on linear programming is a version of the polytope search. However, the polytope search procedure provides more information than a simple Boolean test. The paper proposes a strategy to use the additional information contained in the basis of the linear programming algorithm to obtain other tests. The theoretical results are applied to tessellate several random datasets, and also for much-used datasets in Machine Learning repositories.
URI: http://hdl.handle.net/10553/42858
ISBN: 978-989-8425-98-0
Source: ICPRAM 2012 - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods,v. 2, p. 357-364
Appears in Collections:Actas de congresos
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