Publicación: Aplicación de un Algoritmo Secuencial de Optimizacion SMOreg
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In this work, the application of a predictive model based on the SMOreg regression algorithm, which consists of modeling the behavior of data using statistical regression, is performed. The model was implemented on records of births and deaths in Colombia, which allowed us to predict future behaviors of population growth, aimed at improving decision-making in health and social policies in the country. Our main source of information was the National Administrative Department of Statistics (DANE), from where we obtained the annual information on births and deaths in demographically organized Colombia. Subsequently, the preparation of the data classified by department was carried out to administer them in the statistical model. Once the data were obtained, predictive models were used from Information Technology (IT) as Automated Supervised Methods. Additionally, the Weka data mining tool was used to apply the SMOreg algorithm to the data obtained. The development of this project and its results will serve as an input to improve one of the problems faced by vital statistics; the underreporting from the implementation of IT tools. The application of business intelligence, control panels and dynamic cubes will generate early warnings to obtain reliable data for timely decision making.