| # Amazon Computers |
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| **Task**: Product category classification (co-purchase) |
| **Size band**: medium · **Label type**: semantic |
| **Label column**: `category` · **Converter**: `converters/convert_npz.py` |
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| Amazon co-purchase graph of computer products; 10 category classes, 767 binary bag-of-words review features. |
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| ## Converted graphs (neext/) |
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| | graph | nodes | edges | classes | feature cols | isolated | class counts | |
| |---|---|---|---|---|---|---| |
| | default | 13,752 | 245,861 | 10 | 767 | 281 | 4: 5,158, 8: 2,156, 1: 2,142, 2: 1,414, 7: 818, 3: 542, … | |
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| *Conversion notes*: shchur gnn-benchmark npz; CSR adjacency symmetrized. 767 binary w_* feature columns. |
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| ## Source |
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| - [amazon_electronics_computers.npz](https://raw.githubusercontent.com/shchur/gnn-benchmark/master/data/npz/amazon_electronics_computers.npz) — 31,921,488 bytes, sha256 `736ba1d9fd85eac2…`, fetched 2026-07-23 |
| |
| **License**: MIT (shchur/gnn-benchmark packaging) |
| **Citation**: Shchur, Mumme, Bojchevski, Günnemann. Pitfalls of Graph Neural Network Evaluation. R2L @ NeurIPS 2018. |
| |
| - https://github.com/shchur/gnn-benchmark |
| |
| ## Caveats |
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| - Contains isolated nodes; largest-component filtering will drop some labeled nodes. |
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| --- |
| *Generated by converters/make_cards.py; stats from metadata.json. Raw files: `source/`. NEExT tables: `neext/`.* |
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