| Revista: | Journal of applied research and technology |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000395103 |
| ISSN: | 1665-6423 |
| Autores: | Polat, O1 |
| Instituciones: | 1Akdeniz University, Faculty of Engineering, Antalya. Turquía |
| Año: | 2015 |
| Periodo: | Ago |
| Volumen: | 13 |
| Número: | 4 |
| Paginación: | 443446-443446 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Aplicado, descriptivo |
| Resumen en inglés | This paper proposes a robust regression approach for different classification problems using determination of optimal feature set values. Three different data sets are used to test and evaluate the proposed algorithm. In robust regression stage, the number of vector of regression coefficients is equal to the number of attributes in classification application. In optimization stage, the optimum values of the each of features in classification problem are determined by using genetic algorithm. The high classification accuracy with low number of reference data is the valuable property of proposed method. Simulation results show that proposed classification approach based on robust regression has high accuracy rate |
| Disciplinas: | Ingeniería, Matemáticas |
| Palabras clave: | Ingeniería de control, Matemáticas aplicadas, Regresión robusta, Clasificación de patrones, Optimización |
| Keyword: | Engineering, Mathematics, Control engineering, Applied mathematics, Robust regression, Pattern classification, Optimization |
| Texto completo: | Texto completo (Ver HTML) |
