  The CHIME/FRB collaboration has recently published a catalog containing about
half a thousand fast radio bursts (FRBs) including their spectra and several
reconstructed properties, like signal widths, amplitudes, etc. We have
developed a model-independent approach for a classification of these bursts
using cross-correlation and clustering algorithms applied to one-dimensional
intensity profiles of the bursts (i.e., to amplitudes as a function of time
averaged over the frequency). Using this algorithm we identified two major
classes of FRBs featuring different waveform morphology, and, simultaneously,
different distribution of brightness temperature. Bursts from one of the
identified cluster have lower brightness temperatures and larger widths than
events from the other cluster. Both groups include bursts from the repeaters
and one-off events.
