search for: dynamictreecut

Hi everybody! Anybody knows how can I get detalied information about clusters after using hclust? The issue is that if I have some items in different clusters, I would like to get the cluster where each item is placed. Taking into account that my data set is too large, it is not useful to have the dendogram or a graphic, and really I need something like a simple table with item label and cluster

Hi, I have produced a dendrogram of categorical data in R using the hclust function, although the input was a dissimilarity matrix produced in SAS, as I have defined my own distances. The dendrogram is fine and I can view and use this. However, I was wondering if there is a method by which I can find out the optimal place to place groups, rather than relying on my visual analysis? I don't

...d Color columns as characters (since they are categorical variables) > dd.daisy<-daisy(myddtable, metric = "gower", stand = FALSE, type = list(character=c("Place","Color"))) Then I clustered using DIANA dd.diana<-diana(dd.daisy) I am trying to cutreeDynamic {dynamicTreeCut} as follows cutreeDynamic(dd.diana, cutHeight = 2, minClusterSize = 1, method = "hybrid",+ distM = dd.daisy,+ deepSplit = (ifelse(method=="hybrid", 1, FALSE)),+ maxCoreScatter = NULL, minGap = NULL,+ maxAbsCoreScatter = NU...

...d Color columns as characters (since they are categorical variables) > dd.daisy<-daisy(myddtable, metric = "gower", stand = FALSE, type = list(character=c("Place","Color"))) Then I clustered using DIANA dd.diana<-diana(dd.daisy) I am trying to cutreeDynamic {dynamicTreeCut} as follows cutreeDynamic(dd.diana, cutHeight = 2, minClusterSize = 1, method = "hybrid",+ distM = dd.daisy,+ deepSplit = (ifelse(method=="hybrid", 1, FALSE)),+ maxCoreScatter = NULL, minGap = NULL,+ maxAbsCoreScatter = NULL, minAbsGap = NULL,+ maxDistToLabel = cutHeight,+ resp...

...some demos, 'help()' for on-line help, or > 'help.start()' for an HTML browser interface to help. > Type 'q()' to quit R. > > [Previously saved workspace restored] > > > library(WGCNA) > Loading required package: impute > Loading required package: dynamicTreeCut > Loading required package: flashClust > > Attaching package: 'flashClust' > > The following object(s) are masked from 'package:stats': > > hclust > > Loading required package: qvalue > Loading Tcl/Tk interface ... 2011-01-03 10:51:18.886 R[5858:60f]...

Dear R-Help, I have a clustering problem with hclust that I hope someone can help me with. Consider the classic hclust example: hc <- hclust(dist(USArrests), "ave") plot(hc) I would like to cut the tree up in such a way so as to avoid small clusters, so that we get a minimum number of items in each cluster, and therefore avoid singletons. e.g. in this example, you can see

Hi all, a user contacted me about a segfault when installing WGCNA package dowloaded from CRAN. I also see a segfault like that on certain installs of R. The package passes all CRAN checks, so presumably this has something to do with the R installation or environment. The R versions here are not the newest but I would guess that this is not an R version issue. I'm attaching two