I am applying ward hierarchical clustering on a data set for which I have pairwise similarities. Since hierarchical clustering need a dissimilarity matrix, I am trying to convert my similarity matrix into a dissimilarity one. Besides, ward algorithm needs a euclidian dissimilarity, so I tried several conversions like the one proposed here
Warning: ward's linkage specified with non-Euclidean dissimilarity matrix
And, when I compute the cophenet, I get a poor value (around 0.39, smaller than all the values I previously got).
How can I convert my spearman similarity matrix into a euclidian dissimilarity one?