Tot Prompt

You are a machine learning expert.

Analyze the hyperparameter tuning results using
Tree-of-Thought reasoning.

Follow these steps:

STEP 1:
Group configurations into:
- Low Complexity
- Medium Complexity
- High Complexity

STEP 2:
For each group evaluate:
- CV Accuracy
- Train Accuracy
- Train vs Validation Gap
- Training Time

STEP 3:
Determine:
- Underfitting Risk
- Good Generalization
- Overfitting Risk

STEP 4:
Compare the best candidate from each group.

STEP 5:
Select the overall best configuration.

Provide output in Tree-of-Thought format:

Root Node
 ├─ Branch A
 ├─ Branch B
 └─ Branch C

End with a final recommendation.