| Full text | |
| Author(s): |
Pereira, L. A. M.
;
Rodrigues, D.
;
Ribeiro, P. B.
;
Papa, J. P.
;
Weber, Silke A. T.
;
IEEE
Total Authors: 6
|
| Document type: | Journal article |
| Source: | 2014 IEEE 27TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS); v. N/A, p. 4-pg., 2014-01-01. |
| Abstract | |
Evolutionary algorithms have been widely used for Artificial Neural Networks (ANN) training, being the idea to update the neurons' weights using social dynamics of living organisms in order to decrease the classification error. In this paper, we have introduced Social-Spider Optimization to improve the training phase of ANN with Multilayer perceptrons, and we validated the proposed approach in the context of Parkinson's Disease recognition. The experimental section has been carried out against with five other well-known meta-heuristics techniques, and it has shown SSO can be a suitable approach for ANN-MLP training step. (AU) | |
| FAPESP's process: | 13/20387-7 - Hyperparameter optimization in deep learning arquitectures |
| Grantee: | João Paulo Papa |
| Support Opportunities: | Scholarships abroad - Research |
| FAPESP's process: | 09/16206-1 - New trends on optimum-path forest-based pattern recognition |
| Grantee: | João Paulo Papa |
| Support Opportunities: | Research Grants - Young Investigators Grants |
| FAPESP's process: | 11/14094-1 - Exploring Multi-labeling Approaches by Optimum-Path Forest |
| Grantee: | Luis Augusto Martins Pereira |
| Support Opportunities: | Scholarships in Brazil - Master |