RT Journal Article
T1 A Fast Multivariate Symmetrical Uncertainty Based Heuristic for High Dimensional Feature Selection.
A1 García Torres, Miguel
A1 Divina, Federico
A1 Gómez, Francisco
A1 Vázquez Noguera, José Luis
A2 Universidad Americana (PY)
A2 Universidad Pablo de Olavide (ES)
AB In classification tasks the increase in the number of dimensions of a data makes the learning process harder. In this context feature selection usually allows to induce simpler classifier models while keeping the accuracy. However, some factors, such as the presence of irrelevant and redundant features, make the feature selection process challenging.
YR 2021
FD 2021
LK http://hdl.handle.net/20.500.14066/3778
UL http://hdl.handle.net/20.500.14066/3778
LA eng
NO CONACYT - Consejo Nacional de Ciencia y Tecnología
DS MINDS@UW
RD 21-nov-2024