Multi-task Classification on Bank (test)
73.8F1 ScoreRMB-CLE-via-LGBM
Evaluation results
| Method | Links | |
|---|---|---|
| RMB-CLE-via-LGBMStrategy=Clustering and Local Ensembling, Base Model=LightGBM2026.02 | 73.8 | |
| ST-LGBMStrategy=Single Task, Base Model=LightGBM2026.02 | 65.4 | |
| DP-LGBMStrategy=Data Pooling, Base Model=LightGBM2026.02 | 64.6 | |
| TaF-LGBMStrategy=Task-at-a-time, Base Model=LightGBM2026.02 | 64.6 | |
| R-MTGBStrategy=Robust Multi-task, Base Model=Gradient Boosting2026.02 | 62 | |
| RMB-CLE-via-MTGBStrategy=Clustering and Local Ensembling, Base Model=Multi-task Gradient Boosting2026.02 | 61.6 | |
| MTGBStrategy=Multi-task, Base Model=Gradient Boosting2026.02 | 60.2 | |
| ST-GBStrategy=Single Task, Base Model=Gradient Boosting2026.02 | 57.1 | |
| DP-GBStrategy=Data Pooling, Base Model=Gradient Boosting2026.02 | 53.2 | |
| TaF-GBStrategy=Task-at-a-time, Base Model=Gradient Boosting2026.02 | 53.2 |