similar to: Cluster validation methods

Hello everybody. I am trying to cluster circular data (data points which are angles), thus i can not use the "dist" function in "mclust" to generate my distance matrix, I am using the function " Dij = 0.5*( 1 - cos(theta_i - theta_j)). The thing is "hclust" will not accept this distance matrix, i tried to put it in a data frame, but again i get an error message

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

Dear R users, I am interested in clustering in R. In SAS we have some criteria for determining the number of clusters using the PROC CLUSTER procedure, which are "CCC" cubic clustering criterion (Sarl 1981), Psuedo F (PSF), and Psuedo T square (PST). My question is do thsese criterion exists in R, I tried to search and got one hit (BIC) in Mclust, which I am aware of, any input is

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 R Community- I am a new user of support vector machines for species distribution modeling and am using package e1071 to run svm() and predict.svm(). Briefly, I want to create an svm model for classification of a factor response (species presence or absence) based on climate predictor variables. I have used a training dataset to train the model, and tested it against a validation data set

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

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 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, I am using fanny and I have estrange results. I am wondering if someone out there can help me understand why this happens. First of all in most of my tries, it gives me a result in which each object has equal membership in all clusters. I have read that that means "the clustering is entirely fuzzy". Looking at the graphics it is really difficult to understand how objects with so

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),

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 @

Hello all, This might have been fixed in later versions (I am using R1.7.0), r-help archive contains messages reporting similar problems but no reports of codes fixes. I have encountered a couple of problems using the silhouette function. one occurs when the clustering contains clusters composed of 1 element (Martin Maechler posted code few months ago that fixes a similar problem that occurs

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

Dear R-list members, I am using the cluster package and by the generation of plot.partition I ran into the problem that an alternative title overlaps the default title. > plot.partition(clara.14,which.plot=2,stand=TRUE, main="Silhouette plot of 14 clusters") The manual states that all optional arguments for clusplot.default may also be supplied to plot.partition(). Altering the

Hi there, In the description of command "pam", it mentions "For datasets larger than (say) 200 observations". Now my dataset is a "54732 by 5" dataframe named "test". When I try to run pam(test,4),it shows " cannot allocate vector of length 1497768547". Is it because the row too big that it can't handle? Thank you!

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,

Hi there, Sorry for the double email. Does R have the packages for the following clustering methods? And if it does, what the commands for them? 1. SOM (Self-organization map) 2. Graph partitioning: 3. Neural network 4. Probability Binning Thank you very much! Linda [[alternative HTML version deleted]]

Hi all, I am running a series of experiments where after manipulating my data I run several clustering algorithms (agnes, diana and a clustering method of my own) on the data. I wanted to determine which clustering method did the best job, so therefore I had defined my own quality measure using two criteria: compactness of the data within the clusters themselves and the amount of seperation

Tried several ways to connect to Internet. Perhaps R help could point me in the right direction to make this connection work. setInternet2(use = TRUE) > download.file(" + http://image.shutterstock.com/display_pic_with_logo/322090/322090,1307359665,10/stock-photo-car-silhouette-for-race-sports-design-vector-version-also-available-in-gallery-78667174.jpg + ", +