I found the problem.
For some reason, when I converted the list object with the data in it to
numeric, the values changed. This resulted in different clustering
results. Once that was fixed, the clustering was the same.
Thanks for the responses!
On Mon, Nov 15, 2010 at 2:37 PM, Peter
Hello,
I am using the hclust function to cluster some data. I have two separate
files with the same data. The only difference is the order of the data in
the file. For some reason, when I run the two files through the hclust
function, I get two completely different results.
Does anyone know
On Mon, Nov 15, 2010 at 2:07 PM, rchowdhury rchowdh...@alumni.upenn.edu wrote:
Hello,
I am using the hclust function to cluster some data. I have two separate
files with the same data. The only difference is the order of the data in
the file. For some reason, when I run the two files
I don't know how the hclust function is implemented, but generally in
hierarchical clustering the result can be ambiguous if there are several
distances of identical value in the dataset (or identical between-cluster
distances occur when aggregating clusters). The role of the order of the
data
Here is the code I am using:
m - read.csv(data_unsorted.csv,header=TRUE)
m - na.omit(m)
cs - hclust(dist(t(m),method=euclidean),method=complete)
ds - as.dendrogram(cs)
In this case, m is a 106x40 matrix of doubles. When I change the order of
the columns, I get different results...
Thanks,
RC
On Mon, Nov 15, 2010 at 2:19 PM, Reshmi Chowdhury
rchowdh...@alumni.upenn.edu wrote:
Here is the code I am using:
m - read.csv(data_unsorted.csv,header=TRUE)
m - na.omit(m)
cs - hclust(dist(t(m),method=euclidean),method=complete)
ds - as.dendrogram(cs)
As Christian said, you may want to
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