# Node Classification on A-computer transductive (test)

Source: [Node Classification on A-computer transductive (test)](<https://www.sota2.com/research/sota/node-classification-on-a-computer-transductive-test>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-02-26T05:28:11.332Z

Evaluation of Node Classification performance on the test split of the A-computer dataset under transductive settings, reporting accuracy and delta metrics.

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

| Scope | Recorded value |
| --- | --- |
| Task | Node Classification |
| Dataset (including any stated split) | A-computer transductive (test) |
| Metric | Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 3 of 3 |
| Coverage | All results currently returned for this benchmark |

Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol.

## Metrics

- [Accuracy](<https://www.sota2.com/research/sota/node-classification-on-a-computer-transductive-test.md?metric=Accuracy>): Higher is better; unit: PERCENT.

- [Delta (MLP)](<https://www.sota2.com/research/sota/node-classification-on-a-computer-transductive-test.md?metric=Delta%20(MLP)>): Higher is better; unit: SCALAR.

- [Delta (GNN)](<https://www.sota2.com/research/sota/node-classification-on-a-computer-transductive-test.md?metric=Delta%20(GNN)>): Higher is better; unit: SCALAR.

## Recorded results

| Method | Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| GLNN | 83.03 | Not recorded | 68fa6c0e1e209131cea31beb |
| SAGE | 82.97 | Not recorded | 68fa6c0e1e209131cea31beb |
| MLP | 67.8 | Not recorded | 68fa6c0e1e209131cea31beb |

### GLNN

Accuracy: 83.03. Result ID: 698ebf4bffc3901de0a0ae6c.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c0e1e209131cea31beb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6c0e1e209131cea31beb.md>)

[Implementation](<https://github.com/snap-research/graphless-neural-networks>)

Recorded evaluation configuration: {"Setting":"transductive"}. This record does not assert independent reproduction.

### SAGE

Accuracy: 82.97. Result ID: 698ebf4bffc3901de0a0ae6a.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c0e1e209131cea31beb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa696b1e209131cea21e93.md>)

[Implementation](<https://github.com/BUPT-GAMMA/CPF>)

Recorded evaluation configuration: {"Setting":"transductive"}. This record does not assert independent reproduction.

### MLP

Accuracy: 67.8. Result ID: 698ebf4bffc3901de0a0ae6b.

[Reporting paper](<https://www.sota2.com/research/paper/68fa6c0e1e209131cea31beb.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa69531e209131cea2191b.md>)

[Implementation](<https://github.com/snap-stanford/ogb>)

Recorded evaluation configuration: {"Setting":"transductive"}. This record does not assert independent reproduction.

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