taxonomy_association
Taxonomy-peaked tags first
For each tag, measure the share of its training occurrences that land in its single most common taxonomy. Tags with the strongest one-taxonomy association are scored first.
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Rolling nightly benchmark compiled from the live operational runs. Best strategy in this bundle: taxonomy_association (0.309062 mean p-adic loss).
For these UMLLR ablations, Avg active params / classification is the mean number of active coefficients touched while classifying one product.
Ordering methods
The ablation keeps the greedy p-adic regressor fixed and changes only the tag ordering heuristic used before coefficient fitting.
battle_elo
Pairwise battle ranking
Ranks tags by fold-local Elo scores estimated from tag battles, while excluding the holdout fold from the ranking fit.
random
Seeded random control
Uses a seeded random shuffle of the training tag vocabulary as a control condition.
frequency
Most common tags first
Ranks tags by how often they appear in the training products.
mean_title_position
Average title position
Ranks tags by their average recorded title position in the training products.
| Strategy | Mean p-adic loss | Δ vs battle_elo | Fold wins | Exact acc. | Prefix-2 acc. | Avg active params / classification |
|---|---|---|---|---|---|---|
| taxonomy_association | 0.309062 | -0.032110 | 5/5 | 45.21% | 60.01% | 1.12 |
| battle_elo | 0.341172 | 0.000000 | 0/5 | 41.14% | 56.59% | 1.38 |
| random | 0.353368 | 0.012195 | 6/25 | 39.71% | 55.17% | 1.43 |
| frequency | 0.369124 | 0.027952 | 0/5 | 39.03% | 54.14% | 2.02 |
| mean_title_position | 0.380633 | 0.039461 | 0/5 | 38.14% | 53.05% | 1.81 |