主成分分析和回归法在高校学费标准评价中的应用  

The application of PCA and PCR method in tuition-made standard in Chinese regular institution of higher education

作　　者：艾灵志[1] 梅正阳[1] 王波[2] 李友[3] 

机构地区：[1]华中科技大学数学与统计学院,湖北武汉430074 [2]华中科技大学电子与信息工程学院,湖北武汉430074 [3]华中科技大学机械科学与工程学院,湖北武汉430074

出　　处：《湖北师范学院学报（自然科学版）》2009年第3期99-103,共5页Journal of Hubei Normal University(Natural Science)

摘　　要：我国高等学校学费合理性问题已经成为社会关注的热点问题。针对影响高校学费标准的多个因素,采用主成分分析法(PCA)提炼出较少的关键指标,这些指标是原来指标的修正和量化,它们不仅充分反映了原指标的信息,而且大大简化了评价体系。然后通过主成分回归法(PCR)计算出各高校的综合得分及排名,最后利用模糊聚类检验法和灰色关联分析法对结果进行了检验,证明了该评价体系的可靠性。Higher education tuition and fees have become a hot issue at present in china. The article directs towards number of factors that related to Higher education tuition and fees, with the application of principal component analysis method and gets some integrative indicators. These indicators are the amendment and quantitative of the original indicators . Not only they re- flect all the information of indicators, but also they simplifies the evaluation system greatly. Then we make use of the principal component regression （PCR） to calculate the comprehensive mark and rating points. At last, with the application of fuzzy cluster analysis and gray correlation analysis to the results of the inspection, it tells us this evaluation system is reliable.

关 键 词：主成分分析 主成分回归 模糊聚类 灰色关联分析 

分 类 号：O212.4[理学—概率论与数理统计]