r - 如何修复 r : 'more cluster centers than distinct data points' 中的 kmeans 错误

Question

当我运行 kmeans 算法时，我收到此错误:

Error in kmeans(x, 2, 15) : 
  more cluster centers than distinct data points.

如何修复此错误？它是什么意思？我认为我的数据点是不同的？

这是我的文件和我用来生成 kmeans 的 r 代码:

rnames.csv : 
"a1","a2","a3"

cells.csv : 
0,1,2,1,4,3,5,3,4

cnames.csv : 
"google","so","test"

cells = c(read.csv("c:\\data-files\\kmeans\\cells.csv", header = TRUE))
rnames = c(read.csv("c:\\data-files\\kmeans\\rnames.csv", header = TRUE))
cnames = c(read.csv("c:\\data-files\\kmeans\\cnames.csv", header = TRUE))

x <- matrix(cells, nrow=3, ncol=3, byrow=TRUE, dimnames=list(rnames, cnames))

# run K-Means
km <- kmeans(x, 2, 15)

Answer 1

修复此问题的方法是使用:

cells = c(read.csv("c:\\data-files\\kmeans\\cells.csv", header = FALSE))
rnames = c(read.csv("c:\\data-files\\kmeans\\rnames.csv", header = FALSE))
cnames = c(read.csv("c:\\data-files\\kmeans\\cnames.csv", header = FALSE))

而不是

cells = c(read.csv("c:\\data-files\\kmeans\\cells.csv", header = TRUE))
rnames = c(read.csv("c:\\data-files\\kmeans\\rnames.csv", header = TRUE))
cnames = c(read.csv("c:\\data-files\\kmeans\\cnames.csv", header = TRUE))