关于3D数据的2D PCA

时间:2012-05-10 12:20:24

标签: r plot pca

鉴于我的输入3D数据位于文件“myFile.txt”中,按

组织
435 43 23
234 23 453
212 45 2345
...

我想在它上面执行PCA,只提取第一个 两个主要部分。什么是最简单的方法 为达到这个?我有R和mdp处理,但我不是 确定我需要执行的命令集 使任何这些有用。

我会欣赏建设性意见,而不是无知 downvote。毕竟,目的是帮助我找到解决方案......

1 个答案:

答案 0 :(得分:3)

在基础R中,推荐的函数是prcomp()。阅读其帮助文件?prcomp

一个例子是:

mod <- prcomp(USArrests, scale = TRUE)

mod是类"prcomp"的对象,特征向量矩阵(主要组件,原始/未缩放)在组件x

> str(mod)
List of 5
 $ sdev    : num [1:4] 1.575 0.995 0.597 0.416
 $ rotation: num [1:4, 1:4] -0.536 -0.583 -0.278 -0.543 0.418 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:4] "Murder" "Assault" "UrbanPop" "Rape"
  .. ..$ : chr [1:4] "PC1" "PC2" "PC3" "PC4"
 $ center  : Named num [1:4] 7.79 170.76 65.54 21.23
  ..- attr(*, "names")= chr [1:4] "Murder" "Assault" "UrbanPop" "Rape"
 $ scale   : Named num [1:4] 4.36 83.34 14.47 9.37
  ..- attr(*, "names")= chr [1:4] "Murder" "Assault" "UrbanPop" "Rape"
 $ x       : num [1:50, 1:4] -0.976 -1.931 -1.745 0.14 -2.499 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : chr [1:50] "Alabama" "Alaska" "Arizona" "Arkansas" ...
  .. ..$ : chr [1:4] "PC1" "PC2" "PC3" "PC4"
 - attr(*, "class")= chr "prcomp"

查看x组件:

> head(mod$x)
                  PC1        PC2         PC3          PC4
Alabama    -0.9756604  1.1220012 -0.43980366  0.154696581
Alaska     -1.9305379  1.0624269  2.01950027 -0.434175454
Arizona    -1.7454429 -0.7384595  0.05423025 -0.826264240
Arkansas    0.1399989  1.1085423  0.11342217 -0.180973554
California -2.4986128 -1.5274267  0.59254100 -0.338559240
Colorado   -1.4993407 -0.9776297  1.08400162  0.001450164

提取组件1和2

> scrs <- mod$x[, 1:2]
> head(scrs)
                  PC1        PC2
Alabama    -0.9756604  1.1220012
Alaska     -1.9305379  1.0624269
Arizona    -1.7454429 -0.7384595
Arkansas    0.1399989  1.1085423
California -2.4986128 -1.5274267
Colorado   -1.4993407 -0.9776297

然后你可以绘制它们等等:

plot(scrs, asp = 1) ## asp = 1 gives equal scaling to x and y axes