Regression on Synthetic two-feature data (Linear, n=300)
0.9859Mean R^2LightGBM, rel-s features
Evaluation results
| Method | Links | ||
|---|---|---|---|
| LightGBM, rel-s featuresSample size (n)=3002025.12 | 0.9859 | 0.0035 | |
| NW + relationsNorm/Embedding Type=L2 norm, Sample size (n)=3002025.12 | 0.9839 | 0.0038 | |
| NW + relationsNorm/Embedding Type=MLP embeddings, Sample size (n)=3002025.12 | 0.9806 | 0.0051 | |
| NW + relationsNorm/Embedding Type=learnable norm, Sample size (n)=3002025.12 | 0.9701 | 0.0069 | |
| NW, no rel-s infoNorm/Embedding Type=learnable norm, Sample size (n)=3002025.12 | 0.8902 | 0.0176 | |
| NW, no rel-s infoNorm/Embedding Type=L2 norm, Sample size (n)=3002025.12 | 0.8861 | 0.0176 | |
| LightGBM, no rel-s infoSample size (n)=3002025.12 | 0.8806 | 0.022 | |
| TabRelSample size (n)=3002025.12 | 0.8668 | 0.2762 | |
| NW, rel-s featuresSample size (n)=3002025.12 | -0.1619 | 0.0868 |