Improved k-nearest neighbor classifier for biomedical data based on convex hull of inversed set of points
Zbigniew Szymanski, Marek Dwulit · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2010
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.