This project contains a Java implementation of median relational generalized learning vector quantization as proposed by Nebel, Hammer, Frohberg, and Villmann (2015, doi:10.1016/j.neucom.2014.12.096). Given a matrix of pairwise distances D and a vector of labels Y it identifies prototypical data points (i.e. rows of D) which help to classify the data set using a simple nearest neighbor rule. In particular, the algorithm optimizes the generalized learning vector quantization cost ...