Predicción de factores clave en el aumento de la demografía en Colombia a través del ensamble de modelos de Machine Learning.

Population ageing is considered to be one of the most significant social phenomena that is transforming economies and societies around the world. According to the World Health Organization (WHO), ageing is on the rise. In Colombia, demographic growth exhibits a natural increase, which shows a notable difference between birth and general mortality rates. According to DANE, in Colombia, natural growth rates denote a precipitous decline over time. The Central and local governments can help with decision-making in order to establish sexual and reproductive health policies. Machine Learning (ML) therefore appears as a support tool, in which there are algorithms that allow creating models to learn from data and identify patterns that aid in supporting government entities in the decision-making process. Based on the above, this work proposes a method for ensemble ML algorithms, which supports decision-making regarding demographic control focused on birth. The prediction method made it possible to show that the decrease in births in Colombia in recent years is due to the change in the priorities of women and men. Women face discrimination and difficulty in accessing and staying in employment due to maternity. Consequently, it is difficult for them to articulate their professional life with the job market. Women have to assume a disproportionate burden of care, which is why they want to have fewer children, namely one or two at most. [ABSTRACT FROM AUTHOR]