12.32 主成分图

借助 autoplotly[21] 可将函数 stats::prcomp 生成的结果转化为交互图形

pca <- prcomp(iris[c(1, 2, 3, 4)])
plot(pca)

library(autoplotly)
autoplotly(pca,
  data = iris, colour = "Species",
  label = TRUE, label.size = 3, frame = TRUE
)
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150-0.10-0.050.000.050.100.15-0.2-0.10.00.10.2
Species(setosa,1)(versicolor,1)(virginica,1)setosaversicolorvirginicaPC1 (92.46%)PC2 (5.31%)

ggfortify [22] 包将主成分分析图转化为静态图形

library(ggfortify)
autoplot(pca, data = iris, colour = 'Species')
主成分分析

图 12.70: 主成分分析

参考文献

[21]
Y. Tang, “Autoplotly: An r package for automatic generation of interactive visualizations for statistical results,” Journal of Open Source Software, vol. 3, 2018,Available: https://doi.org/10.21105/joss.00657
[22]
Y. Tang, M. Horikoshi, and W. Li, ggfortify: Unified interface to visualize statistical results of popular r packages,” The R Journal, vol. 8, no. 2, pp. 474–485, 2016, doi: 10.32614/RJ-2016-060.