Revista: | Polibits |
Base de datos: | PERIÓDICA |
Número de sistema: | 000402968 |
ISSN: | 1870-9044 |
Autores: | Marques, Rayrone Zirtany Nunes1 Coutinho, Luciano Reis1 Borchartt, Tiago Bonini1 Vale, Samyr Beliche1 Silva, Francisco Jose da Silva e1 |
Instituciones: | 1Universidade Federal do Maranhao, Sao Luis, Maranhao. Brasil |
Año: | 2015 |
Periodo: | Jul-Dic |
Número: | 52 |
Paginación: | 17-24 |
País: | México |
Idioma: | Inglés |
Tipo de documento: | Artículo |
Enfoque: | Analítico |
Resumen en inglés | In this paper, Genetic Algorithm (GA) is used to search for combinations of learning algorithms and associated parameters with maximum accuracy. An important feature of the approach is that the GA initial population is formed by using parameter values gathered from ExpDB (a public database of data mining experiments). The proposed approach was implemented in a tool called EMiner, built on top of a grid based software infrastructure for developing collaborative applications in medicine and healthcare domains (ECADeG project). Experiments on 16 datasets from the UCI repository were performed. The results obtained have shown that the strategy of combining the data from ExpDB via GA is effective in finding classification models with good accuracy |
Disciplinas: | Ciencias de la computación, Medicina |
Palabras clave: | Inteligencia artificial, Diagnóstico, Algoritmos genéticos, Minería de datos |
Keyword: | Computer science, Medicine, Artificial intelligence, Diagnosis, Genetic algorithms, Data mining |
Texto completo: | Texto completo (Ver PDF) |