  Gamma-Ray Bursts (GRBs) have been traditionally divided into two categories:
"short" and "long" with durations less than and greater than two seconds,
respectively. However, there is a lot of literature (with conflicting results)
regarding the existence of a third intermediate class. To investigate this
issue, we carry out a two-dimensional classification using the GRB hardness and
duration, and also incorporating the uncertainties in both the variables, by
using an extension of Gaussian Mixture Model called Extreme Deconvolution
(XDGMM). We carry out this analysis on datasets from two detectors, viz. BATSE
and Fermi-GBM. We consider the duration and hardness features in log-scale for
each of these datasets and determine the best-fit parameters using XDGMM. This
is followed by information theoretic criterion-based tests (AIC and BIC) to
determine the optimum number of classes. For BATSE, we find that both AIC and
BIC show preference for two components with close to decisive and decisive
significance, respectively. For Fermi-GBM, AIC shows preference for three
components with decisive significance, whereas BIC does not find any
significant difference between two and three components. Our analysis codes
have been made publicly available.
