{
  "model_type": "random-forest",
  "framework": "sklearn",
  "window": 30,
  "stride": 5,
  "input_shape": null,
  "feature_dim": 45,
  "seed": 42,
  "classes": [
    0,
    1
  ],
  "operating_threshold": 0.09,
  "name": "fall-detector",
  "version": "poc",
  "dataset": "le2i",
  "outputs": [
    "fall_prob"
  ],
  "source": "trained",
  "reacquire": "cd ml && uv run python -m training.train"
}