These low-dimensional approximations are derived as a reconstruction from a set of real reference training examples, called landmarks, which can be used to compile the representation of any unseen test instance.
the ability of making connections between the KDA decisions and the landmarks corresponds to locating the candidate training examples that justify (in the LRP sense) decisions and trigger meaningful linguistic explanations.