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主成分分析又称主分量分析,是指设法将原来变量重新组合成一组新的互相无关的几个综合变量,同时根据实际需要从中可以取出几个较少的综合变量且尽可能多地反映原来变量的信息的统计方法,即设法将原来众多具有一定相关性的指标,重新组合成一组新的互相无关的综合指标来代替原来的指标。主成分分析作为基础的数学分析方法,其实际应用十分广泛,比如人口统计学、数量地理学、分子动力学模拟、数学建模、
Principal component analysis, also known as principal component analysis, refers to trying to reassemble the original variables into a new set of several independent variables that are not related to each other. At the same time, several less synthetic variables can be extracted from them and reflected as much as possible The statistical method of information of variables, that is, trying to replace many of the original ones with a certain number of relevant indicators and recombine them into a new set of new ones that are irrelevant to each other. The principal component analysis as the basis of mathematical analysis methods, its practical application is very wide, such as demography, quantitative geography, molecular dynamics simulation, mathematical modeling,