Author(s)

Qing Guan ¹

Affiliation(s)

¹ Nanchang Normal University of Applied Technology, Nanchang, 330108, China

Corresponding Author

Qing Guan

ABSTRACT

This paper explores the application of decision tree algorithms in the analysis of private university students' online lending behavior. We utilize the decision tree classification algorithm to analyze and predict the risk levels of students' online lending behavior, and employ association rule mining techniques to identify potential risk patterns. Additionally, various data analysis methods are discussed to identify abnormal online lending behavior. The research results indicate that by comprehensively applying these methods, it is possible to effectively identify and prevent online lending risks.

KEYWORDS

Decision Tree Algorithm, Online Lending Behavior, Data Mining, Risk Prediction, Anomaly Detection

CITE THIS PAPER

Qing Guan, Research on the application of decision tree algorithm in private universities. Journal of Artificial Intelligence Practice (2024) Vol. 7: 132-138. DOI: http://dx.doi.org/10.23977/jaip.2024.070120.

REFERENCES

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[3] Zhou Li. A CSSA model based on the decision tree algorithm [J]. computer simulation. 2021,38(05):264-268.
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