Hello,
I am hoping you can help me with a question concerning kmeans clustering
in R. I am working with the following data-set (abbreviated):
BMW Ford Infiniti Jeep Lexus Chrysler Mercedes Saab Porsche
Volvo
[1,] 6 8 2 8 4 5 4 4 7 7
[2,] 8 7 4 6 4 1 6 7 8 5
[3,] 8 2 4 6 3 2 7 4 4 4
[4,] 7 4 4 6 6 1 6 3 5 5
[5,] 6 2 4 5 5 1 3 3 6 3
[6,] 6 7 3 6 5 1 8 4 8 2
[7,] 1 6 6 7 5 2 6 6 5 6
[8,] 3 6 6 4 5 1 4 2 1 1
[9,] 6 7 5 8 4 1 6 6 8 5
[10,] 6 7 5 9 3 1 2 5 1 8
When I try to scale my data and perform kmeans clustering, I get the
following errors:
new <- scale(new)
Error in colMeans(x, na.rm = TRUE) : 'x' must be numeric
> cl <- kmeans(new, 4)
Error in switch(nmeth, { : NA/NaN/Inf in foreign function call (arg 1)
In addition: Warning message:
In switch(nmeth, { : NAs introduced by coercion
This is confusing to me since all of the data is numeric and there are
no missing values. Is there something I need to do to my data to prepare
it for kmeans? I have tried many matrix transformations but nothing has
worked so far.
Your help is much appreciated.
Thanks,
jordan
--
Jordan van Rijn
[EMAIL PROTECTED]
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