摘要
通过对大量的心理学测试量表数据集进行分析和挖掘,从大量测量属性中提取了高效属性子集构建关键决策向量,建立了更具针对性和方向性的心理测评模型.该模型能够更加快速、准确地对大学生心理健康状况进行判断和预测,帮助校方对存在问题的受访者及时实施干预,避免问题恶化.
Through analyzing and mining a large dataset of psychological measurement scales,an efficient attribute subset is extracted from a large number of measurement attributes to construct key decision vectors,and a more targeted and directional psychological assessment model is established.This model can more quickly and accurately judge,predict the psychological health status of college students and help schools implement timely interventions for respondents with problems,and avoid problem deterioration.
作者
张桂杰
王小灿
邢维康
李瑞彤
王帅
逯洋
ZHANG Gui-jie;WANG Xiao-can;XING Wei-kang;LI Rui-tong;WANG Shuai;LU Yang(College of Mathematics and Computer,Jilin Normal University,Siping 136000,China)
出处
《吉林师范大学学报（自然科学版）》
2023年第4期123-130,共8页
Journal of Jilin Normal University:Natural Science Edition
基金
吉林省科技厅科学技术项目(20230101243JC,YDZJ202301ZYTS157)
吉林省教育厅科学技术项目(JJKH20220445KJ,JJKH20220446KJ)
吉林省高等教育教学改革研究课题(20213F20T54004H)。
关键词
心理健康
数据可视化
决策树
psychological health
data visualization
decision tree
