  We consider a class of decoding algorithms that are applicable to error
correction for both Abelian and non-Abelian anyons. This class includes
multiple algorithms that have recently attracted attention, including the
Bravyi-Haah RG decoder. They are applied to both the problem of single shot
error correction (with perfect syndrome measurements) and that of active error
correction (with noisy syndrome measurements). For Abelian models we provide a
threshold proof in both cases, showing that there is a finite noise threshold
under which errors can be arbitrarily suppressed when any decoder in this class
is used. For non-Abelian models such a proof is found for the single shot case.
The means by which decoding may be performed for active error correction of
non-Abelian anyons is studied in detail. Differences with the Abelian case are
discussed.
