I am trying to simultaneously cluster and visualize text documents using Self-organizing maps. Since text documents can be represented in various ways (vector space model, GloVe etc), I am trying to figure out how to tell which representation generates the best map. Measures like Quantization error etc., determine the goodness of the map given a dataset. However, they are not useful for quantitatively telling which representation gives a better output.
Is there a quantitative measure to compare the maps generated using different representations (for example, Tf-idf and GloVe) and tell for which representation the output is better?