中文说明：主成分分析，是考察多个变量间相关性一种多元统计方法，研究如何通过少数几个主成分来揭示多个变量间的内部结构，即从原始变量中导出少数几个主成分，使它们尽可能多地保留原始变量的信息，且彼此间互不相关.通常数学上的处理就是将原来P个指标作线性组合，作为新的综合指标。
English Description：
Principal component analysis is a multivariate statistical correlation methods to study how a few main components to reveal the internal structure of multiple variables, namely a few principal components derived from the original variable examine multiple variables, so that they as much as possible to keep the information of the original variables, and unrelated to each other. mathematical treatment is usually the original P is a linear combination of indicators, as a new comprehensive index.