PCNN Fold 4

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Fold metrics

Metric	Value
Test accuracy	11.04%
Test F1 score	0.0877
Hierarchical loss	0.78706870
P-adic loss (total)	2789.52540000
P-adic loss (mean)	0.60157980
Prime base	83
Hidden layer size	27
Max tags	32
Training samples	18,460
Test samples	4,637

P-adic loss breakdown

Agreement	Count	Share	Cost per mistake	Total contribution
Exact match	512	11.04%	0.000000	0.000000
p^3	179	3.86%	0.000002	0.000313
p^2	546	11.77%	0.000145	0.079257
p^1	618	13.33%	0.012048	7.445783
p^0	2,782	60.00%	1.000000	2782.000000

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 83). Lower values indicate closer predictions in the taxonomy hierarchy. This metric is shared with the umllr model for comparison.