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Theheavens committed Feb 28, 2022
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2 changes: 1 addition & 1 deletion openhgnn/dataset/ohgb.md
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Expand Up @@ -66,8 +66,8 @@ Evaluation metric is Macro-F1 and Micro-F1.
| GTN | 0.5791 | 0.6003 |
| NARS | 0.5470 | 0.6259 |
| HPN | 0.5596 | 0.5703 |
| SimpleHGN | 0.5521 | 0.5635 |
| HAN | 0.5530 | 0.5605 |
| SimpleHGN | | |
| HGT | 0.5440 | 0.5519 |

### Dataset `ohgbn-yelp2`
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4 changes: 3 additions & 1 deletion space4hgnn/README.md
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# Design Space for Heterogeneous Graph Neural Network

Paper: [Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network](https://arxiv.org/abs/2202.09177)

Following [GraphGym](https://github.com/snap-stanford/GraphGym), we release a platform Space4HGNN for designing and evaluating Heterogeneous Graph Neural Networks (HGNN). It is implemented with PyTorch and DGL, using the OpenHGNN package.

## How to run
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### 3 Analyze the results

#### 3.1 Gather all results
#### 3.1 Gather all results

To gather all experiments results, we should run the following command to gather all results into one ``.csv`` file.

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