Yet, under-resourced historical languages, such as Ancient Greek and Latin, often lack enough primary material for certain time periods to properly train machinelearning models (a.k.a., classifiers).
only basic NLP techniques (e.g., checking similarity thresholds over string-and n-gram-shingles), which are independent from an advanced global knowledge or training experience, are applicable for analyzing historical corpora (Büchler et al., 2010).