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PROBLEMS DISCUSSION ON THE APPLICATION OF PCA IN COMPREHENSIVE EVALUATION

机译:PCA在综合评价中的应用问题探讨

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More and more people like to use the method of principle component analysis (PCA) in comprehensive evaluations recently. Many of them use the contribution ratios of variances as the weights to make linear combination. Someone has pointed out that it is not reasonable because of the multiple correlations among the indexes and put forward a few resolving methods, such as only using the first principle component or correcting with the subjective weights of importance. This paper finds out the above-mentioned methods are not efficient to satisfy the requirement of comprehensive evaluations with these methods, and the important place should be given to the notions of evaluation purpose, and the aggregate index plays the key role. The completeness of index system could be improved by using the method of PCA, but the contribution ratios of variances can not be used as the weights. Further it is not appropriate to use the conception of information quantity in the method. Finally, the mentioned principles are illustrated by a figure example.
机译:最近,越来越多的人喜欢在综合评估中使用主成分分析(PCA)方法。他们中的许多人使用方差的贡献率作为权重进行线性组合。有人指出,由于指标之间的多重相关性是不合理的,并提出了一些解决方法,例如仅使用第一个主成分或用主观重要性进行校正。本文发现上述方法不能有效地满足用这些方法进行综合评价的要求,应将评价目的的概念放在重要位置,综合指标起关键作用。采用PCA方法可以提高指标体系的完整性,但不能将方差的贡献率作为权重。此外,在该方法中使用信息量的概念是不合适的。最后,通过一个图形示例来说明所提到的原理。

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