RT Conference Proceedings
T1 Rule extraction from medical data without discretization of numerical attributes
A1 Domínguez Olmedo, Juan Luis
A1 Mata Vázquez, Jacinto
A1 Pachón Álvarez, Victoria
A1 Maña López, Manuel Jesús
AB Association rule mining is a popular technique used to find associations between attributes in a dataset. When using deterministic algorithms, if the attributes have numerical values the usual approach is to discretize them defining proper intervals. But the discretization can notably affect the quality of the rules generated. This work presents a method based on a deterministic exploration of the interval search space without a previous discretization of the numerical attributes. It has been applied to medical data from an atherosclerosis study. The quality of the obtained rules seems to support this method as a valid alternative for this kind of rule extraction.
PB Science and Technology Publications
SN 978-989-8425-88-1
YR 2012
FD 2012
LK http://hdl.handle.net/10272/15427
UL http://hdl.handle.net/10272/15427
LA eng
NO Domínguez-Olmedo, J. L., Mata, J., Pachón, V., & Maña López, M.J. (2012). Rule extraction from medical data without discretization of numerical attributes. En: Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, 397-400. DOI 10.5220/0003784603970400
DS Repositorio Institucional de la Universidad de Huelva
RD 31 may 2026