Hi there
I have been using R to perform kmeans on a dataset. The data is fed in using
read.table and then a matrix (x) is created
i.e:
[
mat - matrix(0, nlevels(DF$V1), nlevels(DF$V2),
dimnames = list(levels(DF$V1), levels(DF$V2)))
mat[cbind(DF$V1, DF$V2)] - DF$V3
This matrix is then taken and
First of all, kmeans doesn't work on distance matrices.
On Mon, 7 Aug 2006, Ffenics wrote:
Hi there
I have been using R to perform kmeans on a dataset. The data is fed in using
read.table and then a matrix (x) is created
i.e:
[
mat - matrix(0, nlevels(DF$V1), nlevels(DF$V2),
dimnames =
well then i dont understand because everything i have read so far suggests that
you use the dist() function to create a matrix based on the euclideam distance
and then the kmeans() function.
If this is incorrect, then any suggestins as to how to do this properly would
be much appreciated.
There are many clustering functions in R and R packages and some
take distance objects whereas others do not. You likely read about
hclust or some different clustering function. See ?kmeans for the
kmeans function and also look at the CRAN Task View on clustering for
other clustering functions:
Thanks. I had a look at that and it says:
Partitioning Clustering:
Functionkmeans()
from package stats provides several algorithms for computing
partitions with respect to Euclidean distance.
?kmeans says the following. Note that x is a matrix of ***data***.
Also look at the examples at the end of the help page if its still
not clear.
Usage:
kmeans(x, centers, iter.max = 10, nstart = 1,
algorithm = c(Hartigan-Wong, Lloyd, Forgy, MacQueen))
Arguments:
x: A
Thanks. i shall have a look see
Gabor Grothendieck [EMAIL PROTECTED] wrote: ?kmeans says the following. Note
that x is a matrix of ***data***.
Also look at the examples at the end of the help page if its still
not clear.
Usage:
kmeans(x, centers, iter.max = 10, nstart = 1,
Thanks everyone for their help so far. I'm very appreciative of the fact that
people have pointed out that I was heading in the wrong direction.
I would be most grateful if someone could look over the following simple
example for me and tell me if this is how to do it.
I'm assuming by data matrix
Thanks everyone for their help so far. I'm very appreciative of the fact that
people have pointed out that I was heading in the wrong direction.
I would be most grateful if someone could look over the following simple
example for me and tell me if this is how to do it.
I'm assuming by data
