PCNN Fold 4

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Fold metrics

Metric	Value
Test accuracy	11.31%
Test F1 score	0.0854
Hierarchical loss	0.79245010
P-adic loss (total)	1473.64560000
P-adic loss (mean)	0.55947065
Prime base	79
Hidden layer size	27
Max tags	32
Training samples	10,638
Test samples	2,634

P-adic loss breakdown

Agreement	Count	Share	Cost per mistake	Total contribution
Exact match	298	11.31%	0.000000	0.000000
p^3	111	4.21%	0.000002	0.000225
p^2	315	11.96%	0.000160	0.050473
p^1	442	16.78%	0.012658	5.594937
p^0	1,468	55.73%	1.000000	1468.000000

Tag Rank vs First-Layer Weight Magnitude

Tag rank vs max first-layer weight magnitude — Scatter plot showing the relationship between tag battle ranking and maximum absolute first-layer weight value across all hidden units. Shows which input features contribute most to the parameter constrained neural network's hidden representations.

About p-adic loss

P-adic loss measures the distance between predicted and true taxonomy using p-adic metric (base 79). Lower values indicate closer predictions in the taxonomy hierarchy. This metric is shared with the umllr model for comparison.