The SED Classifier performs a classification of observed spectral energy distributions (SEDs). An SED in this context consists of a one-dimensional row with an identifier in the first column, and one or more floating-point data values (the features).
The classifier works with two sets of SEDs, a table of observed SEDs, and a table of model (template) SEDs. During classification each observed SED is compared with each model SED and a dissimilarity metric is computed. The full result of the classification process is a rectangular matrix with all the dissimilarities.
A condensed result consists of best three classes with their respective dissimilarity values.
