clustering {comato} | R Documentation |
Clustering maps of a conceptmaps object
Description
clustering
is a convenience function that implements two frequently used ways of clustering conceptmaps directly.
The first is clustering using the MBMM algorithm and the concept matrix, the second is clustering using the PAM algorithm and
the graph similarity matrix.
Usage
clustering(maps, method = c("MBMM", "PAM"), min = 1, max = 10)
Arguments
maps |
A conceptmaps object. |
method |
Either "PAM" or "MBMM", indicating which algorithm should be used. |
min |
The minimal number of components that is tested. For the PAM algorithm, 1 is not allowed. |
max |
The maximal number of components that is tested. |
Value
The return value of either MBM.cluster
or PAM.cluster
, depending on the value of method
.
Examples
## Not run:
#Assuming that there are concept maps in folder "~/maps"
cms = read.folder.tgf("~/maps")
clustering(cms, method="MBMM")
## End(Not run)
[Package comato version 1.1 Index]