The authors compile an ordinal odor strength dataset for over 2,000 molecules from public sources and demonstrate supervised ML prediction of intensity categories, identifying molecular size, polarity, rings, and branching as key drivers via SHAP analysis.
Malik, IEEE Trans
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Machine learning for smell: Ordinal odor strength prediction of molecular perfumery components
The authors compile an ordinal odor strength dataset for over 2,000 molecules from public sources and demonstrate supervised ML prediction of intensity categories, identifying molecular size, polarity, rings, and branching as key drivers via SHAP analysis.