RT Conference Proceedings
T1 On Boosting the Accuracy of Medical Image Diagnosis through Cooperation between Classifiers
A1 Stoean, Catalin
AB Each classifier has special inner workings that conduct to a specific separation between the samples that belong to various classes. Although two classifiers might lead to a similar prediction accuracy, the items from the validation set are not identically classified even if they are trained on the same set of samples. The current research is focused on learning how to use the separations for the validation set as achieved by several classifiers in order to reach a test prediction accuracy that is better than the ones of the individual classification.
YR 2017
FD 2017-07-13
LK http://hdl.handle.net/10630/14218
UL http://hdl.handle.net/10630/14218
LA eng
NO La conferencia forma parte del Ciclo de conferencias sobre técnicas de Machin Learning y tratamiento de imágenes organizado por los Departamentos de Tecnología Electrónica y Matemática Aplicada
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. y Dpto. Tecnología Electrónica
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026