Heterogeneous Behavior Analysis of College Students Based on Outlier Detection
Heterogeneous behavior of college students refers to the behavioral preferences of college students with individual characteristics that are different from others.Aiming at the behavior mining problem of heterogeneous individuals of college students,a heterogeneous behav-ior analysis method based on anomaly detection is proposed.A heterogeneous behavior analysis model is established based on the college stu-dent's performance data and campus one-card data of a university.Principal component analysis,K-Means++,and DBSCAN clustering anal-ysis are used to find the weird points,and the research focuses on the heterogeneous behaviors corresponding to these anomalous points.Even-tually,through detecting anomalies,heterogeneous individuals in academic performance can be identified and further explored whether there is a strong correlation between work and rest patterns and academic performance anomalies.The authenticity of these anomalies is verified from both algorithmic and factual dimensions,firstly,multiple algorithms are used to verify the accuracy of the anomalies;secondly,the credibility of the anomaly data is verified with the help of research on related students.Through this study,the heterogeneous behavioral patterns of col-lege students can be analyzed in depth,providing a basic basis for improving schools'management levels and efficiency.
万方数据
维普
