---
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).