将 data.frame 定义为距离并在 R 中执行层次聚类

Question

ggg <- data.frame(row.names=c("a","b","c","d","e"),var1=c("0","0","0","0","0"),var2=c("1","1","1","1","2"))

ggg_dist <- as.matrix(ggg) %>% as.dist(.)

In as.dist.default(.) : non-square matrix

class(ggg_dist)
[1] "dist"

ggg_dist
Warning message:
In df[row(df) > col(df)] <- x :
  number of items to replace is not a multiple of replacement length

 h_ggg <- hclust(ggg_dist,method="average")

Fehler in hclust(ggg_dist, method = "average") : 
  'D' must have length (N \choose 2).

我想用 ggg 执行层次聚类。 ggg_dist 是由 ggg 构成的 class() 确认的距离。我想用 ggg_dist 进行层次聚类，但这不起作用。它显示上述错误。我该如何解决。

我试过，但是当我尝试调用 ggg_dist.

时出现同样的错误

Answer 1

您可以使用函数 dist:

ggg_dist <- dist(ggg, method = "euclidian")

结果：

ggg_dist
  a b c d
b 0      
c 0 0    
d 0 0 0  
e 1 1 1 1

Answer 2

as.dist()需要方阵或data.frame。您的原始对象 ggg 有 5 行，但只有 2 列。

像下面这样的东西会起作用。

ggg <- data.frame(row.names = c("a", "b"), 
                  var1 = c("0", "0"), 
                  var2 = c("1", "1"))

ggg_dist <- as.dist(ggg)

h_ggg <- hclust(ggg_dist, method="average")
h_ggg
#> 
#> Call:
#> hclust(d = ggg_dist, method = "average")
#> 
#> Cluster method   : average 
#> Number of objects: 2

^{由 reprex package (v0.3.0)}

于 2020-05-27 创建

将 data.frame 定义为距离并在 R 中执行层次聚类

define data.frame as a distance and perform hierarchical clustering in R

r

distance

hclust