A Predictive Model for Fertility Behavior of Women of Childbearing Age: Based on the Apriori Algorithm and Smooth Cut-Point Calculation

Abstract

We combine the Apriori data mining algorithm and smooth cut-point calculation to build a model that uses microscopic individual data to predict fertility behavior. The data of China’s migrant population from 2013 to 2015 are used to predict the reproductive behavior of migrant women. The accuracy of the prediction results is over 84%. The model also quantifies the extent to which the existing characteristics of individuals influence their reproductive behavior. The government can regulate individual fertility behavior based on the quantified scores.