| --- |
| license: mit |
| library_name: xgboost |
| tags: |
| - time-series |
| - time-series-forecasting |
| - gift-eval |
| - xgboost |
| - foundation-models |
| --- |
| |
| # TimeRouter |
|
|
| Trained **XGBoost router** weights for |
| [TimeRouter](https://github.com/UConn-DSIS/TimeRouter), the GIFT-EVAL submission that |
| routes among **4 frozen time-series foundation models** (Chronos-2, FlowState, |
| PatchTST-FM, Sundial) with a margin/diversity gate and a CV-inverse-weighted fallback. |
|
|
| **LB MASE = 0.6746** on the full 97-config GIFT-EVAL test suite. |
|
|
| ## Files |
|
|
| | File | Description | |
| |---|---| |
| | `seed42.json` … `seed46.json` | 5-seed XGBoost OvA ensemble. 305-dim features, 400 trees × depth 8 × lr 0.05 × subsample 0.8, `random_state ∈ {42..46}`, `tree_method="hist"`. | |
| | `pool_metadata.json` | Pool config (`{chronos, flowstate, patchtst_fm, sundial}`), 305-feature column order, and gate thresholds `(tau_m, tau_d) = (0.15, 0.02)`. | |
|
|
| ## Usage |
|
|
| These are the checkpoints loaded by `gift_eval/run_eval.py --ckpt-dir <this folder>` in the |
| [TimeRouter repository](https://github.com/UConn-DSIS/TimeRouter); see its README for the |
| full two-environment setup and run instructions. Requires `xgboost >= 2.x`. |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| ckpt_dir = snapshot_download("nkh/timerouter-v1") |
| # then: python gift_eval/run_eval.py --ckpt-dir $ckpt_dir ... |
| ``` |
|
|
| ## Citation |
|
|
| If you use these checkpoints, please cite the TimeRouter repository |
| (UConn Data Science and Intelligent System (DSIS) Research Lab). |
|
|
