October 2021
Intermediate to advanced
289 pages
8h 31m
Chinese
Content preview from 数据科学中的实用统计学(第2版)
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240
｜
第
7
章
图 7-4：家务数据对应分析的图形化表示
本节要点
•
主成分是预测变量的线性组合（只适用于数值型数据）。
•
在计算主成分时，为了减少冗余，要使成分之间的相关性最小。
•
少量主成分经常可以解释结果变量中的大部分方差。
•
这些少量主成分组成的集合可以用来代替初始的预测变量（数量更多），这样可以
降低数据的维度。
•
有一种与主成分分析表面上很相似的技术，这就是对应分析，它可以用于分类型数
据，但在大数据环境下并不适用。
7.1.5
扩展阅读
如果想详细了解交叉验证在主成分分析中的应用，可以参考
Rasmus Bro
、
K. Kjeldahl
、
A. K. Smilde
和
Henk
A. L. Kiers
的文章“
Cross-Validation of Component Models: A Critical
Look at Current Methods
”。
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