Description: The main purpose of PCA is to use fewer variables to explain most of the variation of the original data will be in our hands a number of highly relevant independent variables into each other or irrelevant variables. Is usually higher than the original number of variables selected less able to explain most of the information in the variation of several new variables, called principal components, and to explain the comprehensive index of information. Thus, principal component analysis is a kind of dimension reduction methods.
- [hPSO] - Particle Swarm Optimization algo abbrevi
- [SPSS] - SPSS integration literature, a statistic
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主成分分析法\3.5.ppt
............\factor.pdf
............\SPSS主成分分析与因子分析.ppt
............\主成份分析法知识.doc
主成分分析法
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