Traditionally, the categorization of individual odors or molecules has relied heavily on the expert sensory perception of human evaluators. However, a paradigm shift is occurring, as evidenced by recent works like those of Sanchez-Lengeling et al. ( ) and ; . These researchers have adopted machine learning techniques to approach odor classification from a Quantitative-Structure-Odor-Relationship standpoint. They aim to establish correlations between chemical descriptors of individual odorants and their associated olfactory families or nuances.