similar to: Silhouette function problem

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 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=

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)

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

Dear all, I am trying (without much success) to use the fuction 'silhouette'. Would anyone encountered that before (or would know where I am wrong ?) Please find below the R ouput. Thanks in advance, L. > s <- silhouette(ct, as.dist(metric)) Error in "[<-"(*tmp*, iC, "sil_width", value = s.i) : number of items to replace is not a multiple of replacement

Hi list, When I was using 'silhouette' from the 'cluster' package to calculate clustering performances, R crashed. I traced the problem to the fact that my clustering labels only have 2's and 3's. when I replaced them with 1's and 2's, the problem was solved. Is the function purposely written in this way so when I have clustering labels, "2" and

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

Hi! >library(cluster) In this lib a function called silhoutte.default is defined than on the R prompt it type >silhouette.default Error: Object "silhouette.default" not found R1.9.0 The same error are at R1.8.1 And I knew that a function silhoutte.default are present. But the same piece of code works in R1.6.2 ??? Eryk Dipl. bio-chem. Eryk Witold Wolski @

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

Hello, In cluster analysis with cluster, how does one colour the silhouette plots ? For example in using pam. There seems to be some problem there. Everything else can be coloured. Thanks, A. Mani Member, Cal. Math. Soc

I was trying to create a multi-color silhouette plot (each cluster a different color) from clusters created by trimkmeans. This works straighforwardly on an object created from pam however my colors are interwoven when I try the same approach on clusters from trimkmeans. I also tried sorting the silhouette object using sortSilhouette which did not solve the problem. If anyone has a suggestion,

Dear All, Is there any existing code for plotting silhouette for kmeans clustering results? Many thanks! Linda [[alternative HTML version deleted]]

Hi, I am having a problem in doing something similar to this example: Suppose I have this vector a, and from it I wish to create 5 other vector each one with less one value than what object a has So I have "a" a<-c(1,2,3,4,5) and I want a1 that shoud have (2,3,4,5) a2 that should have (1,3,4,5) a3 that should have (1,2,4,5) a4 that should have (1,2,3,5) a5 that should have

Hi Suppose we have an object with strings: A<-c("a","b","c","d") Now I do: B<-matrix(A,4,4, byrow=F) and I get a a a a b b b b c c c c d d d d But what I really want is: a b c d b c d a c d a b d a b c How can I do this? thank you A. Dias -- View this message in context:

Hi: I have calculated the Silhouette score and Dunn score after hierarchical clustering for 3 clusters: #Distance measure d <- dist(USArrests, method = "euclidean") #Hierarchical clustering hc <- hclust(dist(USArrests), "ave") #calculating silhouette value for 3 clusters sil<- silhouette(cutree(hc, k=3), d) #calculating Dunn index for 3 clusters clus <- cutree(hc,

Hi, I have this character vector: A<-c("Tell me how many different letter this vector has?") Is there a way with R that it can let me know how many different letters I have on this vector? If I use nchar(A) que gives me the number 50. With this function he is counting all the letters present and also spaces between the words. Can we also not count the spaces between words? Then

Hello everybody: I have just started using R, specifically the clustering packages. Despite the vastness of the functionality of the system, I have found it very flexible and intuitive. It has been great fun to experiment with it. Nevertheless, I am under tight time constraints to complete a cluster analysis of some data and need to come up with a "quick" solution for the following

Dear R user, I am a biochemist/bioinformatician, at the moment working on protein clusterings by conformation similarity. I only started seriously working with R about a couple of months ago. I have been able so far to read my way through tutorials and set-up my hierarchical clusterings. My problem is that I cannot find a way to obtain information on the rooting of specific nodes, i.e. of

Hello all, A question/suggestion: I was wondering if there is a chance of changing stats::cutree to be S3 and use cutree.hclust? For example: cutree <- function(tree, k = NULL, h = NULL,...) { UseMethod("cutree") } cutree.hclust <- stats::cutree # This will obviously need the actual content of stats::cutree This would be nicer for people like me to add new methods to

Hi, I am with a problem on how to do a comparison of values. My script is as follows: repeat{ cat("How many teams to use? (to end write 0) ") nro<-scan(n=1) if(nro==0)break cat("write the", nro, "teams names \n") teams<-readLines(n=nro) if (teams[1]==teams[2)next else print(teams) } On this example I only compare teams 1 name with teams 2 name, and if they