Proposing a features preprocessing method based on artificial immune and minimum classification errors methods
Título del documento: Proposing a features preprocessing method based on artificial immune and minimum classification errors methods
Revista: Journal of applied research and technology
Base de datos: PERIÓDICA
Número de sistema: 000395110
ISSN: 1665-6423
Autores: 1
1
1
Instituciones: 1Islamic Azad University, Department of Computer Engineering, Malayer. Irán
Año:
Periodo: Ago
Volumen: 13
Número: 4
Paginación: 477-481
País: México
Idioma: Inglés
Tipo de documento: Artículo
Enfoque: Aplicado, descriptivo
Resumen en inglés Artificial immune systems that have been inspired from organic immune systems, have drawn many attentions in recent years (and have been considered) as an evolutionary algorithm, and have been applied in different papers. This algorithm can be used in two different areas of optimization and classification. In this paper, an artificial immune algorithm has been applied in optimization problem. In particular, artificial immune systems have been used for computing the mapping matrices and improving features. Comparison of results of proposed method with other preprocessing methods shows the superiority of the proposed method so that in 90% of cases it has the best performance based on different measures. Evaluation measures are including classification rate, variance and compression measure
Disciplinas: Ciencias de la computación
Palabras clave: Procesamiento de datos,
Sistemas inmunes artificiales,
Problemas de optimización,
Algoritmos evolutivos
Keyword: Computer science,
Data processing,
Artificial immune systems,
Optimization problems,
Evolutionary algorithms
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