ANÁLISIS DEL COMPORTAMIENTO DEL ALGORITMO SVM PARA DIFERENTES KERNEL EN AMBIENTES CONTROLADOS
DOI:
https://doi.org/10.15628/holos.2018.5563Palavras-chave:
aprendizaje automático, SVM, kernel, estudio experimentalResumo
En el presente trabajo se realiza una investigación del comportamiento de la técnica de aprendizaje automático SVM en diferentes ambientes controlados, usando cinco kernel. Primero se analiza el comportamiento de los clasificadores ante datos con valores perdidos. Luego se prueban en ambientes con valores ruidosos. La última tarea es el análisis de su comportamiento una vez que se adicionan atributos irrelevantes. Para validar los resultados se realizan pruebas estadísticas no paramétricas. Se encontró que la técnica SVM es muy robusta ante los tres ambientes antes mencionados y el kernel polinómico arrojó los mejores resultados de clasificación.Downloads
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