Discovering Mexican Birth Rate Patterns Using Machine Learning Techniques - Somodevilla, Maria; Cantu, David Limon; Pineda, Ivo; Pérez de Celis, Concepción; Vilariño, Darnes (INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 2015)
In this research, we attempt to discover patterns that describe and predict the birth rate in Mexico by using data mining techniques based on relevant demographic and economic information about Mexico. More than twelve million births data obtained from the General Directorate of Health Information in the period 2008-2013 were analyzed. The acquired knowledge allows us to say that in Mexico the birth rate is affected by the social welfare, education and marginality at county level. Due to the diversity of the population and the large number of socioeconomic factors involved in Mexican society, it is difficult to find general impact factors for this issue. The results of this research are not intended to be definitive but its aim is to provide indicators that may influence decisions about birth control in Mexico.