Reducción de dimensiones para clasificación de datos multidimensionales usando medidas de información
Abstract
El enorme desarrollo tecnológico ha creado un concepto de información con áreas extensas de aplicación para tareas referentes al entrenamiento de sistemas automáticos. Este trabajo propone una metodología basada en el análisis de componentes independientes (ICA), que incluye el uso de medidas de información, para realizar reducción de dimensiones en conjuntos de datos multidimensionales. La metodología usa un principio de relevancia, con el fin de hallar la representación reducida mientras se conserva la estructura relacionada a la información inicial. La metodología se compara y se conjuga con un sistema básico de selección de características cuya función de evaluación usa la medida de entropía logrando mejores resultados en la clasificación.Downloads
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