Ponencia
Measuring the error of linear separators on linearly inseparable data
Autor/es | Aronov, Boris
Garijo Royo, Delia Núñez Rodríguez, Yurai Rappaport, David Seara Ojea, Carlos Urrutia, Jorge |
Departamento | Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII) |
Fecha de publicación | 2009-06 |
Fecha de depósito | 2024-05-06 |
Publicado en |
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ISBN/ISSN | 978-84-92774-11-1 |
Resumen | 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 diferent measures. |
Agencias financiadoras | Ministerio de Educación y Ciencia (MEC). España Junta de Andalucía |
Identificador del proyecto | MTM2008-05866-C03-01
P06-FQM-01649 |
Cita | Aronov, B., Garijo Royo, D., Núñez Rodríguez, Y., Rappaport, D., Seara Ojea, C. y Urrutia, J. (2009). Measuring the error of linear separators on linearly inseparable data. En XIII Encuentros de Geometría Computacional (251-258), Zaragoza (España): Prensas Universitarias de Zaragoza. |
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