基于KPCA的高校学业预警模型及其应用  

A Prediction Model on the Performance of College Students Based on the Kernel Principal Component Analysis

作　　者：万星火[1] 郑俊玲[1,2] 金永超[1] 

机构地区：[1]河北联合大学理学院,唐山063010 [2]河北科技师范学院,秦皇岛064006

出　　处：《数学理论与应用》2013年第4期99-104,共6页Mathematical Theory and Applications

基　　金：河北省高等学校科学技术研究项目(QN20131159);唐山市科技计划项目(13130203Z)

摘　　要：针对高校招生规模扩大,学生整体素质下滑,学业完成情况恶化的教育问题,本文从辅导员的工作角度利用核主成分分析(KPCA)建立大学生学业预警创新管理模型,实现动态定性预警与定量预警相结合,对高校科学、及时、有效的开展学业预警工作具有一定的实践指导意义.Along with the expansion of college enrollment, the overall quality of college students declines, and the performance of the students deteriorates. In this paper, a prediction model on the performance of college students, based on the kernel principal component analysis, is established for the purpose of comprehensive assessment, predic tion and management, so as to effectively improve the students＇ performance.

关 键 词：学业预警 综合评价 核主成分 

分 类 号：O212.1[理学—概率论与数理统计]