Application of Principal Component Method in Student Achievement Analysis Based on R Language
Abstract
The principal component method is a frequently used method in dimensionality reduction, which usually targets data characterized by a certain correlation between variables, so that some major components can be identified from the intricate relationship of things, the redundant parts can be removed, and the new variables identifi ed are mutually unrelated to each other as a comprehensive indicator, so that a large amount of statistical data can be effectively used for quantitative analysis to reveal the This paper introduces the idea of principal components and its application in the analysis of student performance. Principal components play an important role in dimensionality reduction and are a powerful tool for comprehensive multivariate evaluation.
Keywords
Principal component approach; Dimensionality reduction; Performance analysis
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[1] Wang Binhui. Multivariate statistical analysis and R language modeling [M]. Guangzhou: Jinan University Press.2010.
[2] Mi Changlin, Ma Aigong, Zhang Xiaodong, Sun Jingguang, Yang Xuelian. Application of principal component analysis in remote sensing image data[J]. Shandong Land Resources,2013,07:69-71+76.
DOI: http://dx.doi.org/10.18686/ahe.v7i20.9592
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