Publicação: What is the Importance of Selecting Features for Non-Technical Losses Identif cation?
Nenhuma Miniatura disponível
Data
2011-01-01
Orientador
Coorientador
Pós-graduação
Curso de graduação
Título da Revista
ISSN da Revista
Título de Volume
Editor
Ieee
Tipo
Trabalho apresentado em evento
Direito de acesso
Resumo
Although non-technical losses automatic identif cation has been massively studied, the problem of selecting the most representative features in order to boost the identif cation accuracy has not attracted much attention in this context. In this paper, we focus on this problem applying a novel feature selection algorithm based on Particle Swarm Optimization and Optimum-Path Forest. The results demonstrated that this method can improve the classif cation accuracy of possible frauds up to 49% in some datasets composed by industrial and commercial prof les.
Descrição
Palavras-chave
Idioma
Inglês
Como citar
2011 Ieee International Symposium On Circuits And Systems (iscas). New York: Ieee, p. 1045-1048, 2011.
