Utilization of XGBoost for Behavior Analysis of Lottery Purchasers

초록

In this study, we conducted a data-driven analysis of lottery purchase behavior by using the XGBoost algorithm to predict future lottery purchase amounts based on purchase patterns of the previous four weeks. We began by judiciously defining key features including the weekly average purchase amount and variance in purchase amount. Subsequently, we evaluated the proposed method’s performance, finding the predicted future purchase amounts to match the actual purchase amounts. A key strength of this study was the interpretability of feature variables. Through the feature importance score from XGBoost, we found that features that capture impulsive patterns in purchases (e.g., variability in purchase amount) are strongly correlated with future spending, which agrees with conventional behavior analysis. Our study can be extended to the development of early warning systems designed to identify at-risk and potentially addicted purchasers on online lottery platforms.

키워드