similar to: printing hclust with k clusters

I'm sorry if this is a trivial question. My system is R 6.33 on Win98 with basic libraries plus the "cluster" library. I'm using "agnes" and "hclust" functions to perform cluster analysis on big data sets. Looking at the documentation for libraries "mva" and "cluster" I can't find out a function like S-Plus "cutree" to get

Hi, I have the distance matrix computed and I feed it to hclust function. The plot function produces a dense dendrogram as well. But, the cutree function applied does not produce the desired list. Here is the code x=data.frame(similarity_matrix) colnames(x) = c(source_tags_vec) rownames(x) = c(source_tags_vec) clust_tree=hclust(as.dist(x),method="complete") plot(clust_tree)

Hello, I'm having trouble figuring out how to see resulting groups (clusters) from my hclust() output. I have a very large matrix of 4371 plots and 29 species, so simply looking at the graph is impossible. There must be a way to 'print' the results to a table that shows which plots were in what group, correct? I've attached the matrix I'm working with (the whole thing

I try to use the routine cutree to cut a tree (created by hclust) into several groups by specifiing the hight of the cut. a<-1:10 cutree(tree, h=a*100) The Matrix with group meberships returned is ok for most of the hights, but in some cases (as for example h=800 and h=900) the results don't make sense (group membership=0 or 58965231, it looks like the range of data allowed by the data

Hello all, I am using libraries (mva,cluster) to produce dendrograms. With 1000 examples the dendrogram gets too crowded, and i am wondering whether there is an option (which i cannot find) to set the number of leaf nodes, like in matlab, and return the plot and the assignment map examples -> leaf nodes. Any suggestion is appreciated. Thanks Edo

Hello, how can I get the similarity value (i.e., the inner cluster similarity) that was used to cut a hierarchical tree at a specific height? I would appreciate your help! Best regards, Madeleine

Hallo Friedrich, I have read your announcement, downloaded and installed it in R-0.61.3. But now I have problems :) > hc <- hierclust(dist(t(pollen)), method=3) Error in pmatch(x, table) : argument is not of mode character > hc <- hclust(dist(t(pollen))) > members(hc) Error in .Fortran("assgn", n = as.integer(n), nplus1 = as.integer(nplus1), : C/Fortran function not in

Hi! I am newbee to R and I am facing the problem in plotting the dedrogram with lot of objects. The lines and labels are overlapped very badly, and writing the graphic to postscript and zooming there is not helping either. I tried cut.dendrogram method, but getting the error that it doesn't exist even though I get the man pages for it. I would not find any solution in web as well, and I

Hi, I have a gene expression experiment with 20 samples and 25000 genes each. I'd like to perform clustering on these. It turned out to become much faster when I transform the underlying matrix with t(matrix). Unfortunately then I'm not anymore able to use cutree to access individual clusters. In general I do something like this: hc <- hclust(dist(USArrests), "ave")

Dear all, I have a question with regard to the use of hclust. I would like to be able to specify my own distance matrix instead of asking R to compute the distance matrix for me. It is computationally easier for me this way. My question is: How can I get hclust to accept this? Thanks, Ranjan -- *************************************************************************** Ranjan

Full_Name: Anja von Heydebreck Version: 1.3.0 OS: Alpha Unix Submission from: (NULL) (141.14.19.61) Hi, I repeatedly obtained meaningless results from the function 'cutree' in the 'mva' package, when the argument 'h' was greater or equal to the maximum height occuring: > library('mva') > y [,1] [,2] [,3] [,4] [1,] 0 1 -1 1 [2,] 0 -1

Hey, I am running hclust on several different distance matrices and I have a question thats more about labeling. I've been looking for a way to label the edge values on the graph with their distances between them. I've been looking through the documentation and I haven't found anything yet. Anyone know if there is a way to plot 'hclust' graphs with such edge values? Or

Dear All, I have a data, suppose it is an N*M matrix data. All I want is to classify it into, let see, 3 classes. Which method(s) do you think is(are) appropriate for this purpose? Any reference will be welcome! Thanks! Best, Baoqiang Cao

Full_Name: Ivan Egorov Version: 1.8.1 OS: MS Windows 2000, SP4 Submission from: (NULL) (194.186.91.129) V<-t(matrix(scan('C:/V3.dat'),3)) d<-dist(V) hc<-hclust(d) rect.hclust(hc,5) Error message is displayed: Read 24 items Error in rect(m[which[n]] + 0.66, par("usr")[3], m[which[n] + 1] + 0.33, : plot.new has not been called yet Here's my data file

Hi All R-helpers This is my first (but probartly not last ;-) mail to R-help, so hello to everybody. My problem: Is there a way to give colors to the labels (sample labels) in plots for a hclust object for better visualization? I have looked through plot, points, hclust and more but cannot find anything on label color. Anybody know if this is doable? Best regards Jeppe

I've been trying to get plot.hclust to work with a hclust object I created and have not had much success. It seems that there is some "hidden" characteristic of a hclust object that I can't see. This is most easily seen in the following example, where plot.hclust works on one object, but when this object is "dumped" and then re-read, plot.hclust no longer works. Is

Hi All: I am clustering 500 genes using hclust of R. Visualizing cluster membership becomes difficult with so many genes in each cluster...Is there a way of printing the dendrogram in multiple pages so that I can clearly see what is in each cluster? Thanks in advance. Karthi.

library(mva) data(USArrests) hc <- hclust(dist(USArrests), "ave") plot(hc) # OK dump(c("hc"), "tst") rm(hc) source("tst") plot(hc) # Error in plot.hclust(hc) : invalid dendrogram input The same problem occurs with dput/dget --please do not edit the information below-- Version: platform =

Hello List, I am trying to implement a hierarchical cluster using the hclust method agglomerative single linkage method with a small wrinkle. I would like to cluster a set of numbers on a number line only if they are within a distance of 500. I would then like to print out the members of this list. So far I can put a vector: > x<-c(2,10,200,300,600,700) into a distance matrix: >

I'd like to be able to cut dendrograms at a height I specify and then plot the resulting subtrees. I wanted to use the dendrogram object for this purpose because there doesn't seem to be a canned way to cut a hclust object and get a list of hclust objects, but there is a function (cut) that does that for dendrograms. The problem I'm having is that when I plot a dendrogram, I