new file: checkpoints_tree/task1_tr_tree/best_tr_tree.pkl

new file:   checkpoints_tree/task1_tr_tree/model_selection.csv
	new file:   evaluation_outputs/task1_tr_tree/evaluation_train_all_samples.csv
	new file:   evaluation_outputs/task1_tr_tree/evaluation_train_curve.png
	new file:   evaluation_outputs/task1_tr_tree/evaluation_val_all_samples.csv
	new file:   evaluation_outputs/task1_tr_tree/evaluation_val_curve.png
	new file:   evaluation_outputs/task1_tr_tree/harmonic_5mm_1.55Hz_prediction.png
	new file:   scripts_tree/__pycache__/config.cpython-310.pyc
	new file:   scripts_tree/config.py
	new file:   scripts_tree/evaluate.py
	new file:   scripts_tree/predict_single.py
	new file:   scripts_tree/train.py

scripts_tree/config.py

@@ -0,0 +1,50 @@
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from pathlib import Path
+import sys
+
+PROJECT_ROOT = Path(__file__).resolve().parents[1]
+if str(PROJECT_ROOT) not in sys.path:
+    sys.path.insert(0, str(PROJECT_ROOT))
+
+from scripts.config import CORE_FEATURE_NAMES, DataConfig
+
+
+@dataclass
+class TreeModelConfig:
+    candidate_models: tuple[str, ...] = ("extra_trees", "random_forest", "gradient_boosting")
+    random_state: int = 42
+
+
+@dataclass
+class TrainConfig:
+    checkpoint_dir: str = "checkpoints_tree"
+    summary_name: str = "model_selection.csv"
+    best_model_name: str = "best_tr_tree.pkl"
+
+
+@dataclass
+class ExperimentConfig:
+    data: DataConfig = field(default_factory=DataConfig)
+    model: TreeModelConfig = field(default_factory=TreeModelConfig)
+    train: TrainConfig = field(default_factory=TrainConfig)
+
+
+def make_experiment_config() -> ExperimentConfig:
+    return ExperimentConfig()
+
+
+def checkpoint_dir(config: ExperimentConfig) -> Path:
+    path = config.data.project_root / config.train.checkpoint_dir / "task1_tr_tree"
+    path.mkdir(parents=True, exist_ok=True)
+    return path
+
+
+def evaluation_dir(config: ExperimentConfig) -> Path:
+    path = config.data.project_root / "evaluation_outputs" / "task1_tr_tree"
+    path.mkdir(parents=True, exist_ok=True)
+    return path
+
+
+FEATURE_NAMES = CORE_FEATURE_NAMES