How can I do an SVM classification when I only have a distance matrix (pairwise matrix)?
Edited: I want to classify my data in two groups: healthy and sick. My original data are histograms (which are extracted from images), so I measure the distance (euclidean and others) between all the histograms and I obtain a distance matrix, I know how to use a clustering method with distance matrix (K-medoids clustering for example) but how can I classify my subjects using a supevised classification method when my original data are histograms?
other additions: I do know which subject is sick or healthy. I measure a variable for each subject, so a subject -> a histogram. and I want to know how well can the variable separates healthy subjects from sick patients. For the clustering part that I already did, I used k-medoids (PAM algorithm) and as the input I used the distance matrix that I obtained by measuring the distances between all histograms and I want to do the same thing with a supervised classification method.
Is there a supervised classification method that can classify objects like histograms (distributions)