基于粗糙集的主成分聚类方法
Principal Component Clustering Method Based on Rough Set
摘要: 针对当前大规模高维数据难处理以及传统的二支聚类造成误分类等问题。本文首先根据主成分分析方法对数据进行降维处理，并将粗糙集理论与聚类相结合，提出了基于粗糙集的主成分聚类方法。最后，对陕西省内11个城市的25个经济指标进行实验分析，根据经济指标的聚类结果将城市进行三划分，提高了聚类的准确率。
Abstract: In view of the difficulties in processing large-scale high-dimensional data and the misclassification caused by traditional two-way clustering, firstly, this paper reduces the dimension of the data according to the principal component analysis method, and combines the rough set theory with clustering, and the principal component clustering method based on rough set are proposed. Finally, 25 economic indicators of 11 cities in Shaanxi Province are experimentally analyzed. According to the clustering results of economic indicators, the cities are divided into three groups, which improves the accuracy of clustering.
文章引用：花遇春, 杨璇, 熊文丹. 基于粗糙集的主成分聚类方法[J]. 计算机科学与应用, 2022, 12(5): 1378-1388. https://doi.org/10.12677/CSA.2022.125137

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