In addition, the wrapper’s stepwise backward elimination, which finds the optimal model by removing the least relevant factors, was applied. Decision trees, logistic regression, neural networks, and random forest were applied to develop a predictive model among the numerous data mining techniques. In this study, 2975 elderly people from low-income families were extracted using the 13th-year data of the Korea Welfare Panel Study (2018). Hence, this study aims to select the factors related to depression in low-income seniors identified in previous studies and to develop a prediction model. That said, it has been vital to focus on preventing depression in the elderly in advance. Among the common chronic diseases, the elderly tends to have a high incidence of depression. Korea is showing the fastest trend in the world in population aging there is a high interest in the elderly population nationwide.
