I have a question regarding Wards method of hierarchical clustering. I used Gower Distance to create a dissimilarity matrix from an event log. I want to agglomerate it with Ward's method.
Lets suppose i have the following dissimilarity matrix as a starting point:
I now want to use Wards Method to find clusters. At the beginning, every single node is a cluster, so my clusters are 1,2,3,4,5. Now, in the first step, I want to add the two nodes to a cluster where the increase in variance is lowest.
My problem is: I do not have any values for the nodes themselves, only for the distances (the matrix you see in the picture is "all I have"). For calculating variance, I need the mean of each cluster, but I do not have them.
Is it even possible to use wards method in this case? Will I need to use other clustering methods, like Single Linkage?
Any help is greatly appreciated as I do not know how to continue.