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fix: clarify cross_validation (#644)

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Yuante Li
2025-02-26 17:52:30 +08:00
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parent e3d6361ae9
commit 21dfcdabf8
1 changed files with 3 additions and 2 deletions
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rdagent/components/coder/data_science/raw_data_loader/prompts.yaml
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@@ -262,8 +262,9 @@ spec:
- It should be called before dataset splitting.
3. Dataset Splitting
- The dataset returned by `load_data` is not split into training and testing sets, so the dataset splitting should happen after calling `feat_eng`.
- Use cross-validation if possible, as it provides a more robust evaluation of the model's performance.
- The dataset returned by `load_data` is not pre-split. After calling `feat_eng`, split the data into training and test sets.
- If feasible, apply cross-validation on the training set (`X_transformed`, `y_transformed`) to ensure a reliable assessment of model performance.
- Keep the test set (`X_test_transformed`) unchanged, as it is only used for generating the final predictions.
4. Submission File:
- Save the final predictions as `submission.csv`, ensuring the format matches the competition requirements (refer to `sample_submission` in the Folder Description for the correct structure).