similar to: selecting optimal cluster validation score

Hi everybody! I try to implements Self-Organizing Maps with R and the Kohonen package. I have made an algorithm that try differents width and height. For each step, Silhouette index, Davies-Bouldin index and Dunn index are computed. However, there is always after severals minutes a *Runtime error* appears on the window: Microsoft visual c++ runtime library "this application has requested

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 am using Silhouette to estimate the number of clusters in a microarray dataset. Initially, I used the iris data to test my piece of code as follows: library(cluster) data(iris) mydata<-iris[,1:4] maxk<-15 # at most 15 clusters myindex<-rep(0,maxk) # hold the si values for each k clusters mdist<-1-cor(t(mydata)) #dissimlarity

Basic question: Is it correct to assume that when using cutree to set the # clusters (say k=4), cutree determines the clusters by the largest distances among all potential clusters? I've read the R help for cutree and am using it to define the number of groups to obtain Dunn Index scores (using clValid library) for cluster analysis (using Euclidean Distance and Ward's method) More

Hi! I just discovered that cutree() and cut.dendrogram() do not assign the same cluster numberings when called on the same tree. More specifically, cutree() assigns cluster numbers by order of appearance in the data, while cut.dendrogram() sorts clusters by height (see example below). I guess this is for historical reasons? I'm hit by this difference when I want to get a vector of cluster

Sorry for the long message. I'm doing my best to try to explain myself. I have fitted a spline to my data, I have fitted a spline, filled in the missing data by replicating the spline coefficients associated to the last node. I obtained a number of dendograms by different combination of distance and link-method by calling DIST and AGNES. The agglomerative coefficient is very high (~ 0.99) for

Hi, I am using code below to get a plot that will show me on the X axis the number of clusters and on the Y axis the cluster average widths. However I am getting this error: Error in summary(silhouette(cutree(d, x), dist(iris[, -5])))$si.summary : $ operator is invalid for atomic vectors the code I am using is: avgs<-sapply(1:20,function(x) summary(silhouette(cutree(d,x),

Dear R users, I am mailing you about the graphical output of silhouette (cluster package) From the example of silhouette in help(silhouette): > ar <- agnes(ruspini) > si3 <- silhouette(cutree(ar, k = 5), # k = 4 gave the same as pam() above + daisy(ruspini)) > plot(si3, nmax = 80, cex.names = 0.5) from which one may conclude that group 1 is composed by

Hi! In the example: hc <- hclust(dist(USArrests), "ave") dend1 <- as.dendrogram(hc) dend2 <- cut(dend1, h=70) Do the branches "Branch 1", "Branch 2", "Branch 2"...in dend2$upper str(dend2$upper) --[dendrogram w/ 2 branches and 4 members at h = 152] |--[dendrogram w/ 2 branches and 2 members at h = 77.6] | |--leaf "Branch 1" (h=

On Tuesday 28 June 2005 15:30, r-help-request at stat.math.ethz.ch wrote: Re : 37. Re: A. Mani : colours in Silhouette (Mulholland, Tom) > > Message: 37 > Date: Tue, 28 Jun 2005 09:08:24 +0800 > From: "Mulholland, Tom" <Tom.Mulholland at dpi.wa.gov.au> > Subject: Re: [R] A. Mani : colours in Silhouette > To: <a_mani_sc_gs at vsnl.net>, <r-help at

Hi. I did write those functions, and sent them (I thought) to one of the R maintainers to see whether they would be appropriate for inclusion (because I'd seen some requests on the mailing lists). However, I'm happy to post them -- I should have thought of it before. WARNING: I've tested these functions on some data arising in my work and also on the USArrests data that comes with

I'm fairly new to the silhouette functionality in the cluster package, so apologize if I'm asking something naive. If I run the 'agnes(ruspini)' example from the silhouette section of the cluster package vignette, and assign colours to clusters, two clusters have what appear to be incorrect colours in the silhouette plot. library(cluster) data(ruspini) ar<- agnes(ruspini)

Dear All,i applied "NbClust", to my data to find optimum number of clusters, and got following resultsNow, i don't know how to read these results. more precisely, i would like to know, how to see which method is more precise for my data considering these index values.your help is needed...thanks in advance Eliza Botto > dput(Eliza)structure(list(All.index = structure(c(2, 3, 4, 5,

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

Hi Suppose you have the code below. The result I get from the cat function is from the avgs object. Now, I have 30 diferent objects like this and I wish to make a summary table, something like: Avgs1 Avgs2 Avgs3 i= 2 average= 0.515983i i= 2 average= 0.746983 i= 2 average= 0.2665983 i= 3 average=

Hallo Sebastian, >>>>> "SP" == Sebastian P?lsterl <sebp at k-d-w.org> >>>>> on Sun, 14 Jun 2009 14:04:52 +0200 writes: SP> Hello Martin, SP> I plotting the silhouette of a clustering and storing it as png. When I SP> try to store the image as png the bars are missing. The bars are plotted SP> when I use x11 or

Hi All, Except the "Rand Index", "Dunn Index" and "Silhouette width", are there other cluster validation methods in R? Could you please also specify the function? Thanks! [[alternative HTML version deleted]]

Dear R Helpers, I read carefully the documentation and all postings on the hclust and cutree functions, however some aspects of the tree ordering and cluster assignment performed by these functions remain unclear to me, so I would very much appreciate your help in making sure I get them right. Here is an example, with values chosen to illustrate the problems. I have a set of five profiles

Hello to all, I still have this doubt. I'd like to colour the different labels of my dendrogram each one with a different colour. How can I do? I guess I could do using *edgetext* and then *t.col* or* lab.col* but I don't know how to add edgetext to my dendrogram. Can you help me please? Example: require(graphics); require(utils) hc <- hclust(dist(USArrests), "ave") (dend1

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