On 9 May 2008, at 09:12, Jordan van Rijn wrote:
> 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
Probably the data is stored as factor instead of numeric.
Try coercing by as.numeric(new)
hth, Ingmar
>> 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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> PLEASE do read the posting guide http://www.R-project.org/posting-
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> and provide commented, minimal, self-contained, reproducible code.
Ingmar Visser
Department of Psychology, University of Amsterdam
Roetersstraat 15
1018 WB Amsterdam
The Netherlands
t: +31-20-5256723
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