Modern wide field radio surveys typically detect millions of objects. Manual determination of
the morphologies is impractical for such a large number of radio sources. Techniques based
on machine learning are proving to be useful for classifying large numbers of objects. The
self-organizing map (SOM) is an unsupervised machine learning algorithm that projects a
many-dimensional dataset onto a two-or three-dimensional lattice of neurons. This
dimensionality reduction allows the user to visualize common features of the data better and�…