All papers about spectral clustering use similarity matrix as the input to spectral clustering algorithm.
Is it also possible to use pairwise distance matrix? I haven't seen any version of spectral clustering code which would use parwise distance. I am implementing spectral clustering in matlab and it has the function pdist and the output of this function is pairwise distance matrix.
Similarity or Affinity Matrix gives an idea about the closeness of these data points with respect to each other. Distance on the other hand gives the measure of dis-similarity w.r.t each other. The easiest and most frequently used way of using pairwise distances for Similarity Matrix is to use a Gaussian kernel to get the affinity measure.
For points a and b, let D = pdist(a,b) give you the pairwise distance. Then the similarity for your matrix can be obtained as sim_ab = exp-(D/f) where f is a scaling factor.
