Displaying 20 results from an estimated 5000 matches similar to: "rect.hclust fails when k is specified (PR#6740)"
2000 Jul 20
3
printing hclust with k clusters
howdy R friends,
I've searched CRAN but to no avail... I'm trying to use mva's hclust and
print out for say 10 clusters in batch. How do I do this? It's unclear if
I can use cutree.
thanks,
John Strumila
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2002 Feb 20
1
plot.hclust: strange behaviour with "manufactured" hclust object
I've been trying to get plot.hclust to work with a hclust object I
created and have not had much success. It seems that there is some
"hidden" characteristic of a hclust object that I can't see. This is
most easily seen in the following example, where plot.hclust works on
one object, but when this object is "dumped" and then re-read,
plot.hclust no longer works. Is
2009 Nov 16
3
Cluster analysis: hclust manipulation possible?
I am doing cluster analysis [hclust(Dist, method="average")] on
data that potentially contains redundant objects. As expected,
the inclusion of redundant objects affects the clustering result,
i.e., the data a1, = a2, = a3, b, c, d, e1, = e2 is likely to
cluster differently from the same data without the redundancy,
i.e., a1, b, c, d, e1. This is apparent when the outcome is
visualized
2003 Sep 30
2
dump/source problem with hclust object (PR#4361)
library(mva)
data(USArrests)
hc <- hclust(dist(USArrests), "ave")
plot(hc) # OK
dump(c("hc"), "tst")
rm(hc)
source("tst")
plot(hc) # Error in plot.hclust(hc) : invalid dendrogram input
The same problem occurs with dput/dget
--please do not edit the information below--
Version:
platform =
2005 Jan 25
2
Plotting hclust with lot of objects
Hi!
I am newbee to R and I am facing the problem in plotting
the dedrogram with lot of objects. The lines and labels are overlapped very
badly, and writing the graphic to postscript and zooming there is not helping
either. I tried cut.dendrogram method, but getting the error that it doesn't
exist even though I get the man pages for it.
I would not find any solution in web as well, and I
2004 May 19
7
Help with hclust() and plot()
Hi
When I use plot(hclust(dist..)...)...) etc to create a dendrogram of a
hierarchial cluster analysis, I end up with a vertical tree. What do I
need to do to get a horizontal tree?
Also, my users are used to seeing trees who's leaves all "end" at the
same place (eg. Like in minitab). Is this possible in R?
Thanks
Mick
Michael Watson
Head of Informatics
Institute for Animal
2012 May 24
4
Manually modifying an hclust dendrogram to remove singletons
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
2004 May 10
3
Colouring hclust() trees
I have a data set with 6 variables and 251 cases.
The people who supplied me with this data set believe that it falls
naturally into three groups, and have given me a rule for determining
group number from these 6 variables.
If I do
scaled.stuff <- scale(stuff, TRUE, c(...the design ranges...))
stuff.dist <- dist(scaled.stuff)
stuff.hc <- hclust(stuff.dist)
2013 May 21
2
Cambiando limites en hclust()
Buenas tardes a todos,
Estoy interesado en cambiar los límites del eje y en un dendograma
construído utilizando la función hclust(). A continuación un ejemplo:
hc <- hclust(dist(USArrests), "ave")
plot(hc)
Hasta aquí todo bien. Si quisiera cambiar los límites del eje "y" de c(0,
200)? Al usar
plot(hc, ylim = c(0, 200))
no observo efecto alguno.
Qué puedo hacer?
2011 Apr 01
2
hc2Newick is different than th hclust dendrogram
Hi R helpers... I am having troubles because of the discrepancy
between the dendrogram plotted from hclust and what is wrote in the
hc2Newick file. I've got a matrix C:
> hc <- hclust(dist(C))
> plot(hc)
with the:
> write(hc2Newick(hc),file='test.newick')
both things draw completely different "trees"...
I have also tried with the raw distance matrix D and
2012 Mar 29
2
hclust and plot functions work, cutree does not
Hi,
I have the distance matrix computed and I feed it to hclust function. The
plot function produces a dense dendrogram as well. But, the cutree function
applied does not produce the desired list.
Here is the code
x=data.frame(similarity_matrix)
colnames(x) = c(source_tags_vec)
rownames(x) = c(source_tags_vec)
clust_tree=hclust(as.dist(x),method="complete")
plot(clust_tree)
2009 Nov 17
1
hclust too slow?
Hi,
I am new to clustering in R and I have a dataset with approximately 17,000
rows and 8 columns with each data point a numerical character with three
decimal places. I would like to cluster the 8 columns so that I get a
dendrogram as an output. So, I am simply creating a distance matrix of my
data, using the 'hclust' function, and then plotting the results (see below,
my data is
2012 Oct 11
2
extracting groups from hclust() for a very large matrix
Hello,
I'm having trouble figuring out how to see resulting groups (clusters)
from my hclust() output. I have a very large matrix of 4371 plots and 29
species, so simply looking at the graph is impossible. There must be a
way to 'print' the results to a table that shows which plots were in
what group, correct?
I've attached the matrix I'm working with (the whole thing
2011 Sep 13
2
help with hclust
Hello,
how can I get the similarity value (i.e., the inner cluster similarity) that was used to cut a hierarchical tree at a specific height?
I would appreciate your help!
Best regards,
Madeleine
2011 Sep 16
1
cutree() and rect.hclust(): different labelling of classes
I've found that while cutree() and rect.hclust() make the same classes
for a given height in the dendrogram, the actual labeling of the classes
is different. For example, both produce the same 4 classes but
class 1 according to cutree() is class 4 according to rect.hclust().
Would it be possible that future versions provide the same labeling?
rect.hclust() is useful to display the classes
2003 Nov 03
2
hclust doesn't return merge details
Dear R-users,
I tried to receive the merge details of a clustering by using the
summary function of hclust.
For illustration I use the Longley data as done by Prof Ripley (Wed 11
Apr 2001)
d <- dist(longley.y)
d <- d/max(d)
hc <- hclust(d, "ave")
But instead of getting a matrix for $merge I get:
>summary(hc)
Length Class Mode
merge 30 -none- numeric
2012 Apr 30
2
Generate Dendrogram
Hi
I have a distance matrix which is computed by user defined method. I
would like to plot the dendrogram. I would like to use different color
and want the leaves laying down bottom.
The script like this. I am not familiar with R. I followed the example
shown in
http://stat.ethz.ch/R-manual/R-devel/library/stats/html/dendrogram.html
dist.obj <- as.dist(matrix.distance)
hc.obj <-
2003 Nov 04
1
hclust doesn't return merge details [Solved]
Thanks to Andy and Thomas,
Reading help(hclust) more carefully would have done it but sometimes you do not
see the wood for the trees...
So hc$merge does exactly what I want.
I have never been aware of the command str to get the structure of an R-object. It
seems pretty useful to me.
Thanks,
Arne
> -----Original Message-----
> From: Liaw, Andy [mailto:andy_liaw at merck.com]
>
2011 Jan 12
3
Problems creating a PNG file for a dendrogram: "Error in plot.window(...) : need finite 'xlim' values"
Has anyone successfully created a PNG file for a dendrogram?
I am able to successfully launch and view a dendrogram in Quartz. However, the dendrogram is quite large (too large to read on a computer screen), so I am trying to save it to a file (1000x4000 pixels) for viewing in other apps. However, whenever I try to initiate a PNG device, I get a "need finitite 'xlim' values"
2003 Sep 24
5
splitting clusters
Hi All:
I am clustering 500 genes using hclust of R. Visualizing cluster
membership becomes difficult with so many genes in each cluster...Is there
a way of printing the dendrogram in multiple pages so that I can clearly
see what is in each cluster?
Thanks in advance.
Karthi.