[R] questioin about cluster in R
TEMPL Matthias
Matthias.Templ at statistik.gv.at
Wed Apr 19 09:11:42 CEST 2006
Hello,
> -----Ursprüngliche Nachricht-----
> Von: r-help-bounces at stat.math.ethz.ch [mailto:r-help-
> bounces at stat.math.ethz.ch] Im Auftrag von Jane Ren
> Gesendet: Dienstag, 18. April 2006 21:33
> An: R-help at stat.math.ethz.ch
> Betreff: [R] questioin about cluster in R
>
> Hi,All.Sorry for the group mail.
> I recently met a question and I have struggled on that for a while but
> failed to found the solution.
> I have a distance matrix as below.
>
> ---
> 0 35 33 9 36
> 35 0 10 32 51
> 33 10 0 30 49
> 9 32 30 0 35
> 36 51 49 35 0
> -------------------
> I want to do cluster with average method.
> ----
> rown<-c("A", "B", "C", "D", "E")
> mydistMatrix <- read.table("D:\\5.distance",row.names = rown)
>
> mydistObj<-as.dist(mydistMatrix, diag = FALSE, upper = FALSE)
>
> mycluster <- hclust(mydistObj,method="average")
>
> bmp(filename = " D:\\5_ave.bmp")
> plot(mycluster,hang=-1)
>
> dev.off()
> ---
> The result is something like
>
> |
> 20|
> | _______________
> 15| | |
> | | |
> 10| | -------------------
> | | | (intersection) |
> 5 | | ------- |
> | | | | ----------
> 0 | | | | | |
>
> E A D B C
>
> Then I want to set a threshold to cluster them. Say 5.
## Make an executable example (!)...
## threshold 1
set.seed(123)
a <- dist(rnorm(100))
ah <- hclust(a)
cutree(ah, h=1)
> But I don't know when A-D distance is larger than 5 or not.
## for 70-44 distance:
d <- ah$height[which(abs(ah$merge) == c(70,44))[1]]
d > 1 ## FALSE
## for 91-95:
d <- ah$height[which(ah$merge == c(91,95))[1]]
d > 1 ## TRUE
I don't know if this is exactly what you want, but probably this helps a little bit.
Best,
Matthias
> I can draw a line to see whether A-D distance is larger than 5 or but.
> When
> when the dataset is large, it is difficult to tell.
>
> So I wonder whether there is a way in R to display the distance value at
> the
> intersection so that we can see the exact value of it.
> or there is way to show or save the distance matrix after the average
> algorithm.
> Thanks a lots!
> Focus
>
> _________________________________________________________________
> Don't just search. Find. Check out the new MSN Search!
More information about the R-help
mailing list