RT Conference Proceedings
T1 A Distributed Solution to the PTE Problem
A1 Giráldez, J. Ignacio
A1 Elkan, Charles
A1 Borrajo Millán, Daniel
AB A wide panoply of machine learning methods is available for application to the Predictive Toxicology Evaluation (PTE) problem. The authors have built four monolithic classification systems based on Tilde, Progol, C4.5 and naive bayesian classification. These systems have been trained using the PTE dataset, and their accuracy has been tested using the unseen PTE1 data set as test set. A Multi Agent Decision System (MADES) has been built using the aforementioned monolithic systems to build classification agents. The MADES was trained and tested with the same data sets used with the monolithic systems. Results show that the accuracy of the MADES improves the accuracies obtained by the monolithic systems. We believe that in most real world domains the combination of several approaches is stronger than the individuals. Introduction The Predictive Toxicology Evaluation (PTE) Challenge (Srinivasan et al. 1997) was devised by the Oxford University Computing Laboratory to test the suitability ...
PB American Association for Artificial Intelligence (AAAI)
YR 1999
FD 1999-03
LK http://hdl.handle.net/10016/7370
UL http://hdl.handle.net/10016/7370
LA eng
NO Proceeding of: AAAI Spring Symposium on Predictive Toxicology, AAAI Press, Stanford, March 1999
DS e-Archivo
RD 27 abr. 2024