dendrogram

I have a dendrogram in R that I just can't get it right. I'll show you what the problem is, please check this: http://img.photobucket.com/albums/v699/rica01/Rplot-1.png How can I make the labels on the leaves, bigger and more spaced between them? Thanks. -Ricardo Solution: use the set function, with the "labels_cex" parameter from the dendextend package. # install.packages("dendextend") library(dendextend) dend <- as.dendrogram(hclust(dist(USArrests[1:5,]))) # Like: # dend <- USArrests[1:5,] %>% dist %>% hclust %>% as.dendrogram # By default, the dend has no text size to it (showing only the

I have implemented an algorithm to solve the problem of clustering in a graph. I used the python library "python-graph" to represent the graph. Now, at each step of my computation (the algorithm is iterative) I have to draw a part of the dendrogram. In fact, the algorithm is divisive, in the sense that starting from the original graph calculates the clusters. Now, I don't know what to use to draw the dendrogram (someone suggested PIL, but I'm looking for something easy and I don't know how to use PIL)... can you suggest something and show me how to do plot with it? Note: I read other questions

I am trying to cluster a data matrix produced from scientific data. I know how I want the clustering done, but am not sure how to accomplish this feat in R. Here is what the data looks like: A1 A2 A3 B1 B2 B3 C1 C2 C3 sample1 1 9 10 2 1 29 2 5 44 sample2 8 1 82 2 8 2 8 2 28 sample3 9 9 19 2 8 1 7 2 27 Please consider A1,A2,A3 to be three replicates of a single treatment, and likewise with B and C. Sample1 are different tested variables. So, I want to hierarchically cluster this matrix in order to see the over all differences between the columns, specifically I will be making a dendrogram (tree

I have five points and I need to create dendrogram from these. The function 'dendrogram' can be used to find the ordering of these points as shown below. However, I do not want to use dendrogram as it is slow and result in error for large number of points (I asked this question here Python alternate way to find dendrogram ). Can someone points me how to convert the 'linkage' output (Z) to the "dendrogram(Z)['ivl']" value. >>> from hcluster import pdist, linkage, dendrogram >>> import numpy >>> from numpy.random import rand >>> x = rand(5,3) >>> Y = pdist(x) >>> Z = linkage(Y) >>> Z array([[ 1.

I have three matrices to compare. Each of them is 5x6. I originally wanted to use hierarchical clustering to cluster the matrices, such that the most similar matrices are grouped, given a threshold of similarity. I could not find any such functions in python, so I implemented the distance measure by hand, (p-norm where p=2) . Now I have a 3x3 distance matrix (which I believe is also a similarity matrix in this case). I am now trying to produce a dendrogram. This is my code, and this is what is wrong. I want to produce a graph (a dendrogram if possible) that shows clusters of the matrices that

I have a dendrogram in R. It is based on hierachical clustering using hclust. I am colouring labels that are different in different colours, but when I try changing the labels of my dedrogram (to the rows of the dataframe the cluster is based on) using dendrogram = dendrogram %>% set("labels", dataframe$column) the labels are replaced, but in the wrong positions. As example: My dendrogram looks like this: ___|___ | _|_ | | | | 1 0 2 when I now try changing the labels like specified above, the labels are changed, but they are applied from left to right in their order in the dataframe. If we