Speaker
Abdelaziz Berrado
(Mohammed V University in Rabat, EMI)
Description
PRIM is a Bump Hunting algorithm traditional used in a supervised learning setting to find regions in the input variables subspace while being guided by the data analyst, that are associated with the highest or lowest occurrence of a target label of a class variable.
We present in this work a non-parametric PRIM-based algorithm that involves all the relevant attributes for rule generation and that provides an additional post processing step for rule pruning and organization.
| Classification | Both methodology and application |
|---|---|
| Keywords | XAI, bump hunting, PRIM |
Primary author
Abdelaziz Berrado
(Mohammed V University in Rabat, EMI)
Co-author
Mrs
Rym Nassih
(Mohammed V University in Rabat, EMI)