Métodos de análisis estadístico con datos dispersos
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En este artículo se presentan las principales características de algunas metodologías para derivar modelos de predicción o clasificación cuando se tienen muchos datos. Dentro de estos se describen las redes neuronales, bosques aleatorios, árboles de decisión, árboles altamente aleatorizados (extra trees) y método de regresión asistida por patrón de contraste (CPXR). Técnicas que han sido utilizadas para derivar modelos de predicción de retención de agua, clasificación de imágenes, clasificación de suelos, determinación de las principales variables que intervienen en un proceso.
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