Table 1 Results of CSMLP classification models.
From: Predicting odor from vibrational spectra: a data-driven approach
Work | Dataset(Features) | Classifier | F1 Score | Precision | Recall |
|---|---|---|---|---|---|
This work | Subset-IGD(PCA-Reduced VS_IMG) | Â | 0.3425 | 0.3074 | 0.386 |
Subset-IGD(GS_VS) | Â | 0.3341 | 0.2995 | 0.377 | |
Subset-IGD(DFF) | CSMLP | 0.4064 | 0.3632 | 0.4614 | |
Subset-IGD (PCA-Reduced VS_IMG concatenated to PCA-Reduced DFF) | Â | 0.3576 | 0.3547 | 0.3604 | |
IGD(DFF) | Â | 0.4083 | 0.3603 | 0.4710 | |
Saini et al.20 | IGD (DFF) | Random Forest | 0.3221 | 0.3757 | 0.2819 |
Binary Relevance | 0.3523 | 0.3563 | 0.3483 | ||
Classifier Chain | 0.3267 | 0.3745 | 0.2930 |
