similar to: cutreeDynamic error

I am having difficulty getting the dynamic tree cut package to work. Given the data table "myddtable" LengthPlaceColorAge5HRed224ABlue205WGreen243GRed222GBlue236WGreen255ARed194H Blue23 I created a similarity matrix using DAISY and Gower metric and specified Place and Color columns as characters (since they are categorical variables) > dd.daisy<-daisy(myddtable, metric =

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, 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

I am using the function cutreeHybrid from the package dynamic Tree Cut and I need a list of the resulting clusters but I do not know how to get it. [[alternative HTML version deleted]]

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