Simultaneous approach to fuzzy cluster, principal component and multiple regression analysis
Simultaneous approach to fuzzy cluster, principal component and multiple regression analysis
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模糊聚类、主成分和多元回归分析的同步方法
DOI：
10.1109/ijcnn.1999.830864
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发表时间：
1999
期刊：
影响因子：
--
通讯作者：
T. Miyoshi
中科院分区：
文献类型：
--
作者：
A. Yamakawa;K. Honda;H. Ichihashi;T. Miyoshi
Hathaway和Bezdek的模糊c-回归模型[FCRM]（1993）被认为是聚类和多元回归的同时分析。在高维环境下，通过数据集的划分，由于样本固有的稀疏性，回归技术在合理的样本量下表现不佳。本文提出了一种同时进行聚类、主成分分析和多元回归分析的方法。
Hathaway and Bezdek's fuzzy c-regression models [FCRM] (1993) is regarded as a simultaneous analysis of clustering and multiple regression. In high dimensional setting, by the partitioning of data set, the regression techniques do not perform well for reasonable sample sizes because of the inherent sparsity of samples. This paper proposes a simultaneous approach to the clustering, principal component analysis and multiple regression analysis.