Article
Minimizing the error of linear separators on linearly inseparable data
Author/s | Aronov, Boris
Garijo Royo, Delia ![]() ![]() ![]() ![]() ![]() ![]() ![]() Núñez Rodríguez, Yurai Rappaport, David Seara, Carlos Urrutia, Jorge |
Department | Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII) |
Publication Date | 2012 |
Deposit Date | 2020-06-19 |
Published in |
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Abstract | Given linearly inseparable sets R of red points and B of blue points, we consider several
measures of how far they are from being separable. Intuitively, given a potential separator
(‘‘classifier’’), we measure its quality ... Given linearly inseparable sets R of red points and B of blue points, we consider several measures of how far they are from being separable. Intuitively, given a potential separator (‘‘classifier’’), we measure its quality (‘‘error’’) according to how much work it would take to move the misclassified points across the classifier to yield separated sets. We consider several measures of work and provide algorithms to find linear classifiers that minimize the error under these different measures. |
Funding agencies | Ministerio de Educación y Ciencia (MEC). España |
Project ID. | MTM2008-05866-C03-01
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Citation | Aronov, B., Garijo Royo, D., Núñez Rodríguez, Y., Rappaport, D., Seara, C. y Urrutia, J. (2012). Minimizing the error of linear separators on linearly inseparable data. Discrete Applied Mathematics, 160 (10-11), 1441-1452. |
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