%0 Conference Proceedings
%4 sid.inpe.br/banon/2002/11.28.12.12
%2 sid.inpe.br/banon/2002/11.28.12.12.30
%@doi 10.1109/SIBGRAPI.2001.963036
%T Performance evaluation of prototype selection algorithms for nearest neighbor classification
%D 2001
%A Sánchez, J. S.,
%A Barandela, R.,
%A Alejo, R.,
%A Marqués, A. I.,
%E Borges, Leandro Díbio,
%E Wu, Shin-Ting,
%B Brazilian Symposium on Computer Graphics and Image Processing, 14 (SIBGRAPI)
%C Florianópolis, SC, Brazil
%8 15-18 Oct. 2001
%I IEEE Computer Society
%J Los Alamitos
%P 44-50
%S Proceedings
%1 SBC - Brazilian Computer Society
%K attern Recognition; Classification; Prototype Selection; Nearest Neighbor.
%X Prototype selection is primarily effective in improving the classification performance of Nearest Neighbor (NN) classifier and also partially in reducing its storage and computational requirements. This paper reviews some prototype selection algorithms for NN classification and experimentally evaluates their performance using a number of real data sets. Finally, new approaches based on combining the NN and the Nearest Centroid Neighbor (NCN) of a sample [3] are also introduced
%@language en
%3 44-50.pdf
%O The conference was held in Florianópolis, SC, Brazil, from October 15 to 18.