| Full text | |
| Author(s): |
Pereira, Luis A. M.
;
Papa, Joao Paulo
;
de Souza, Andre N.
;
Kuzle, I
;
Capuder, T
;
Pandzic, H
Total Authors: 6
|
| Document type: | Journal article |
| Source: | 2013 IEEE EUROCON; v. N/A, p. 5-pg., 2013-01-01. |
| Abstract | |
Since the beginning, some pattern recognition techniques have faced the problem of high computational burden for dataset learning. Among the most widely used techniques, we may highlight Support Vector Machines (SVM), which have obtained very promising results for data classification. However, this classifier requires an expensive training phase, which is dominated by a parameter optimization that aims to make SVM less prone to errors over the training set. In this paper, we model the problem of finding such parameters as a metaheuristic-based optimization task, which is performed through Harmony Search (HS) and some of its variants. The experimental results have showen the robustness of HS-based approaches for such task in comparison against with an exhaustive (grid) search, and also a Particle Swarm Optimization-based implementation. (AU) | |
| FAPESP's process: | 12/14158-2 - Commercial Losses Characterization in Power Distribution Systems Using Optimum-Path Forest and Evolutionary Approaches |
| Grantee: | André Nunes de Souza |
| Support Opportunities: | Regular Research Grants |
| 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 |