From: Don Eduardo Miranda (miranda@di.fct.unl.pt)
Date: Sat 28 Dec 2002 - 17:47:37 EST
Message-id: <007901c2ae3d$02287880$f801000a@pong>
Hi. The clustering algorithms present in R assume i have a data matrix.
However my data is expressed as a graph (nodes and weights between these
nodes). Generally i can work around this by replacing the weights as
similarities in the dissimilarity matrix, but as R clustering algorithms
like MClust work from the original data matrix i cant do this in this case.
Is there any way i could obtain a suitable matrix to replace the data matrix
starting just from the knowledge i have from the graph? I have no idea if
this is even mathematically feasible as you seem to lose information when
going from the data matrix to the dissimilarity matrix.
Well, thanks
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