1- PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
2- PLEASE, first _read_ help for kmeans (?kmeans) function before using
function.
> On 22 May 2017, at 05:33, θ ” <yarmi1...@hotmail.com> wrote:
>
> hi:
> I need to extract the text contexts of top 1 group after clustering.
> But I have no idea how to sort the cluster size then extract the contexts of
> top 1 clusters.
There isn’t a _top_ cluster for kmeans algorithm. There are _only_ clusters!
>
> here is my cluster code:
>
>> file <- read.csv("SiC CMP.csv", header = TRUE)
We don’t know what is in file$Main.IPC.
>> cluster_k<-length(unique(file$Main.IPC))
>> cl <- kmeans(IPC_Dtm , cluster_k)
What is IPC_Dtm?
>
>
> I have tried use��
>
>> sort(cl$size, decreasing=T)
if you read the documentation, you would know cl$size means the number of
points in each cluster. So, why do you sort them?
> [1] 341 107 104 80 51 22 15 11 10 8 8 5 5 5 4 4 4 3
> 3 2 2
> [22] 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1
> 1 1 1
> [43] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
>
> But I have no idea how to extract the contexts of top 1 cluster.
If you read the _Value_ section of kmeans documentation, you will have an idea
how to extract context by using cl$cluster.
>
>
> Eva
>
> [[alternative HTML version deleted]]
>
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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