Application of Data Mining Combined With K-Means Clustering Algorithm in Enterprises' Risk Audit
Sharif Uddin Ahmed Rana · Advances in logistics, operations, and management science book series · 2024
The financial risk management mechanism of enterprises can be more complete through exploration in the application effect of data mining technology combined with K-means clustering algorithm in enterprise risk audit. Hence, K-means clustering algorithm is introduced to study the paperless status of electronic payment in the trading process of e-commerce enterprises. Additionally, a risk audit model of e-commerce enterprises is implemented based on K-means algorithm combined with Random Forest Light Gradient Boosting Machine (RF-LightGBM). In this model, the actual operation process of data preparation, data preprocessing, model construction, model application and evaluation are the payment flow in the transaction process of e-commerce enterprises by using big data analysis technology. Eventually, the performance of the model is evaluated by simulation.