  Gamma-ray bursts (GRBs) are commonly attributed to the demise of massive
stars or the merger of binary compact objects. However, their varied emission
characteristics strongly imply the existence of multiple GRB classes based on
progenitor types, radiation mechanisms, central engines etc. This study
utilizes unsupervised clustering with the Nested Gaussian Mixture Model
algorithm to analyze {\it Fermi} and BATSE GRB data, identifying four classes
(A, B, C, and D) based on duration, spectral peak, and spectral index,
comprising approximately 70\%, 10\%, 3\%, and 17\% of the dataset,
respectively. Classes A and B consist of long GRBs, C mainly short GRBs, and
class D encompasses both short and long GRBs. Using the spectral index,
$\alpha$, for the differentiation of radiation models, it is found that classes
B and C align with photospheric emission models, while A and D predominantly
show synchrotron radiation characteristics. Short GRBs predominantly exhibit
photospheric emission, whereas long GRBs show consistency with synchrotron
emission. Overall, 63\% of the total bursts exhibit $\alpha$ profiles
indicative of synchrotron emission, with the remaining 37\% associated with
photospheric emission. The classes were further examined for their progenitor
origins, revealing that classes A and D demonstrate a hybrid nature, while
classes B and C are predominantly associated with collapsar and merger origins,
respectively. This clustering analysis reveals distinct GRB classes, shedding
light on their diversity in radiation, duration and progenitor.
