RNA residues come in a plethora of geometric conformational shapes, some of which are very common and some of which are rather rare. In this contribution we extend the previously developed clustering algorithm MINT-AGE in order to find within a large database rare conformational clusters of very small sizes. To this end in the MINT step we replace the previous nonparametric circular mode hunting by a parametric version. In validation, this allows to identify conformational classes of sizes \(\ge 2\) via statistical unsupervised learning on the gold standard database, hand curated by the Richardson Laboratory.