Using p-adic coefficients to predict taxonomy from tags
The umllr (Universal Machine Learning Linear Regression) model assigns p-adic integer coefficients to product tags and uses them to predict taxonomy encodings. Each taxonomy path is encoded as a p-adic integer (base 71), and tags are fitted to minimize p-adic distance on training data.
| Fold | Accuracy | F1 | P-adic loss (mean) | Details |
|---|---|---|---|---|
| 0 | 43.85% | 0.4563 | 0.35587078 | View details → |
| 1 | 44.28% | 0.4551 | 0.33218043 | View details → |
| 2 | 45.58% | 0.4744 | 0.31500944 | View details → |
| 3 | 41.59% | 0.4474 | 0.34913012 | View details → |
| 4 | 44.56% | 0.4809 | 0.35212978 | View details → |