摘要
为了提高高维数据集合数据挖掘效率,探讨了采用数据变换进行数据维数消减的方法及其应用,提出了一个通用的数据变换维数消减模型,给出了应用主成分分析方法计算模型中的数据变换矩阵的方法,相应的数据变换应用实例表明,通过数据变换用相当少的变量来捕获原始数据的最大变化是可能的.
The data dimension reduction is the main method that can enhance the data mining efficiency based on higher-dimension data set. In this paper, the method and the application using data transformation to reduce data dimension are studied. A general data transformation model is proposed. How to compute the data transformation matrix of the model with the principal component analysis method is introduced explicitly. And a application example about this method is given too. The example indicates that it＇s possible to capture the maximum variations of the original variables with fewer variables.
出处
《武汉大学学报（理学版）》
CAS
CSCD
北大核心
2006年第1期73-76,共4页
Journal of Wuhan University:Natural Science Edition
基金
软件工程国家重点实验室开放基金资助项目(SKLSE05-09)
关键词
数据挖掘
维数消减
主成分分析
数据变换
data mining
dimension reduction
principal component analysis
data transformation
