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Proceedings Paper

Improved k-nearest neighbor classifier for biomedical data based on convex hull of inversed set of points
Author(s): Zbigniew Szymański; Marek Dwulit
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Paper Abstract

We present the improved k-nearest neighbor (kNN) classifier and its application for biomedical data. Our method limits the number of considered neighbors from the training set by selecting only those samples that are neighbors in the computed Voronoi diagram of the training set plus classified sample. The method is based on convex hull calculation of inversed set of points. A very important feature of presented method is the stability of results (in terms of recall and precision values) in broad range of the neighborhood size as opposed to the regular kNN classifier. The classification performance was confirmed on three biomedical benchmark data sets.

Paper Details

Date Published: 14 September 2010
PDF: 8 pages
Proc. SPIE 7745, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2010, 774510 (14 September 2010); doi: 10.1117/12.873054
Show Author Affiliations
Zbigniew Szymański, Warsaw Univ. of Technology (Poland)
Marek Dwulit, Warsaw Univ. of Technology (Poland)


Published in SPIE Proceedings Vol. 7745:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2010
Ryszard S. Romaniuk, Editor(s)

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