similar to: Plotting Clustering Groups Separately

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

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 There, I'm working on some cluster analyses on a large data-set using hclust with Wards method and Manhattan (city block) distance measures. I've created dendrograms to illustrate the clustering criteria, but would like to create a plot to examine for the classic elbow criterion to use in determining the best number of clusters. Ideally I'd like to plot percent variance explained

Thanks a lot, Michael! I cc to R-help, where this question really belongs {as the 'Subject' suggests itself...} -- please drop 'bioconductor' from CC'ing further replies. >>>>> "michael" == michael watson (IAH-C) <michael.watson at bbsrc.ac.uk> >>>>> on Thu, 17 Jun 2004 09:16:59 +0100 writes: michael> OK, admittedly it

Hi, this is rather a (presumed) bug report than a question because I can solve my personal statistical problem by working with hclust instead of agnes. I have done a complete linkage clustering on a dist object dm with 30 objects with agnes (R 1.8.0 on RedHat) and I want to obtain the partition that results from a cut at height=0.4. I run > cl1a <- agnes(dm, method="complete")

Hi, this is rather a (presumed) bug report than a question because I can solve my personal statistical problem by working with hclust instead of agnes. I have done a complete linkage clustering on a dist object dm with 30 objects with agnes (R 1.8.0 on RedHat) and I want to obtain the partition that results from a cut at height=0.4. I run > cl1a <- agnes(dm, method="complete")

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")

On Tue, 26 Feb 2019 16:37:39 +0100 David Jehin <bedou210977 at gmail.com> wrote: > THANK YOU FOR YOUR REPLY > > THE RESULT : > KVNO Principal > ---- > -------------------------------------------------------------------------- > 1 HOST/samba4 at FSS.LAN (des-cbc-crc) > 1 HOST/samba4.fss.lan at FSS.LAN (des-cbc-crc) > 1 SAMBA4$@FSS.LAN (des-cbc-crc) >

compiled samba version : 4.8.5 and my distribution is: debian stretch 9.6 I said that when I join the domain, restarting the machine takes the GPO, the other restart does not take the gpo computer. Thanks for your help Le mar. 26 févr. 2019 à 17:11, Rowland Penny via samba < samba at lists.samba.org> a écrit : > On Tue, 26 Feb 2019 16:37:39 +0100 > David Jehin <bedou210977 at

THANK YOU FOR YOUR REPLY THE RESULT : KVNO Principal ---- -------------------------------------------------------------------------- 1 HOST/samba4 at FSS.LAN (des-cbc-crc) 1 HOST/samba4.fss.lan at FSS.LAN (des-cbc-crc) 1 SAMBA4$@FSS.LAN (des-cbc-crc) 1 HOST/samba4 at FSS.LAN (des-cbc-md5) 1 HOST/samba4.fss.lan at FSS.LAN (des-cbc-md5) 1 SAMBA4$@FSS.LAN (des-cbc-md5) 1

Ladies and Gentlemen, As Johan Lindberg points out, the documentation for handling dendrograms is sparse....Does anyone know who is responsible for or working on development of tree methods and objects? I've written a couple of scripts for my own use to translate between parenthetical (A(B(CD))) or binary A00 B10 C11 D11 tree formats and cluster objects in R, but as an inexperienced

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,

Hello, I've been clustering my data using hclust and cutting the resulting tree with cutree. Separately, I visualize the clusterings with heatmap. Is it possible to have the dendrogram on the heatmap reflect the cutree results? That is, instead of having one large dendrogram, it would have 4 or 25 in the example below. Any guidance on if that's possible or not, and what kinds of

I'm using R (2.4.1) and Hmisc (3.3-1), and I'd like to plot confidence intervals using xYplot and smean.cl.normal (or smean.cl.boot) from Hmisc. You can do that using the summarize() to produce a new data.frame and then plot with xYplot, or by specifying method=smean.cl.normal in the xYplot. Both produce very similar graphs in all trivial examples I've tried, but not in the attached

When I use the function cutree(), the numbers of the clusters are not in the same order as the plotted dendrogram. Is there any way of sorting them so that they match the tree? Is it possible to plot a dendrogram horizontally, preferably with the branches to the right? This would enable some practical composite plots, e.g. labels that were an entire table with several columns of information, or

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 use the following clustering methods and get the corresponding dendrograms for single, complete, average, ward and kmeans clustering. This gives the dendrograms, but doesn't show the calculation-way. My question: is there a possibility to show this calculation steps (cluster steps) in matrix or graphical form? Mit freundlichen Gr??en Ralph Modjesch

I have a training set of data for known classes with 5 observations of 12 variables for each class. I want to use this information to classify new data into classes which are known to be different to those in the training set but each new class may contain one or more observations. The distribution of within class distances is expected to be similar for all classes and this is found to be the

I think are looking for the function 'cutree' from package mva checkout its documentation: > require(mva) > ?cutree pleanty of examples to do what you want. ############################################################################# Hi R lovers! I am using the agnes function of the package cluster to compute a hierarchical clustering. I'd like to know if somebody has ever

Hello I try today to install samba 4.13.1 ? ./configure run without error Make run without error Make Check Failed Debian 10.6 Also all required Packages are installed -- # cat summary = Failed tests = == samba4.blackbox.demote-saveddb == command: PYTHON=python3 /usr/src/samba-4.13.1/testprogs/blackbox/demote-saveddb.sh $PREFIX_ABS/demote