{
  "schema_version": 1,
  "backend": "python",
  "task_type": "regression",
  "analysis": "prediction",
  "target": "outcome",
  "target_unit": "synthetic_unit",
  "target_definition": {
    "sample_unit": "independent synthetic row",
    "averaging_period": "not applicable",
    "prediction_time": "features available before prediction"
  },
  "features": [
    "x1",
    "x2",
    "treatment"
  ],
  "categorical_features": [],
  "id_column": "id",
  "split": {
    "column": "dataset",
    "train": "train",
    "val": "val",
    "test": "test"
  },
  "missing": {
    "policy": "error",
    "sentinels": [
      -999
    ]
  },
  "models": [
    {
      "id": "baseline",
      "learner": "baseline_mean",
      "parameters": {}
    },
    {
      "id": "forest",
      "learner": "random_forest",
      "parameters": {
        "n_estimators": 32,
        "max_depth": 6,
        "min_samples_leaf": 3,
        "max_features": 1.0
      }
    }
  ],
  "selection_metric": "rmse",
  "seed": 20261029,
  "row_limits": {
    "train": 1000,
    "val": 1000,
    "test": 1000
  },
  "explanation": {
    "methods": [],
    "features": [
      "x1",
      "treatment"
    ],
    "validation_rows": 8,
    "background_rows": 8,
    "permutation_repeats": 2,
    "pdp_points": 4
  },
  "execution": {
    "purpose": "engineering_replay"
  }
}