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LPM93/italian-cuisine-gat
italian-cuisine-gat is a machine learning model from LPM93. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as cc-by-4.0.
This repository preserves compact evaluation and interpretation artifacts from Leonardo Pacciani-Mori's Italian regional-cuisine graph study. It does not distribute trained checkpoints or source recipe records.
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Updated Aug 1, 2026
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From the Hugging Face model README
This repository preserves compact evaluation and interpretation artifacts from Leonardo Pacciani-Mori's Italian regional-cuisine graph study. It does not distribute trained checkpoints or source recipe records.
Companion code and full provenance notes:
https://github.com/LeonardoPaccianiMori/portfolio-italian-cuisine
Portfolio project:
https://leonardo.pm/projects/italian-cuisine/
| Approach | Accuracy | Macro F1 | Weighted F1 |
|---|---|---|---|
| Four macro-regions | 59.49% | 52.98% | 58.79% |
| Twenty individual regions | 20.26% | 18.50% | 21.45% |
| Hierarchical classifier | 22.31% | 17.82% | 21.59% |
The committed JSON files contain the complete recorded metrics. signature_ingredients_val.json contains exploratory ingredient-gradient results from the validation split.
The classifier used a heterogeneous GAT over recipe, ingredient, and step nodes. Its registered relations connected recipes to ingredients and steps, and steps to ingredients. The richer Neo4j representation also contained tools and sequential step relations, but those were not consumed by the recorded GAT.
The signature analysis used raw ingredient-embedding gradient norms. It was not attention extraction, integrated gradients, or a causal explanation method.
These files are retained as transparent portfolio evidence and may support methodological review or comparison. They are not a deployable model release.
The original aggregate result and interpretation files are licensed under CC BY 4.0. See LICENSE.md.
Attribution: “Italian Cuisine Graph Analysis, Leonardo Pacciani-Mori.”
No rights to omitted recipe corpora are granted.
@misc{pacciani_mori_italian_cuisine_graph,
author = {Leonardo Pacciani-Mori},
title = {Italian Cuisine Graph Analysis and Regional Classification},
year = {2025},
url = {https://github.com/LeonardoPaccianiMori/portfolio-italian-cuisine}
}