基于主成分分析的国家竞争力研究
Research on Competitiveness of Some Countries Based on Principal Component Analysis and K-Means Clustering
摘要:
本文选取42个个国家的20个评价指标，首先用反映信息无序度的信息熵对指标初步筛选，保留贡献率较高的12个指标，达到降维的效果。再用主成法求得能代表大多数信息的主成分，用K-means法对结果进行聚类。最后得到国家竞争力的排名与分类。
Abstract:
In this paper, 20 evaluation indicators from 42 countries are selected. Firstly, the information entropy reflecting the degree of information disorder is used to preliminarily screen the indicators, and 12 indicators with high contribution rate are retained, thus achieving the effect of dimensionality reduction. Then the principal components representing most information are obtained by the principal components analysis and the results are clustered by K-means method. Finally, the ranking and classification of national competitiveness are obtained.
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