Explanation:
The primary reason for placing the CrossValidator inside the Pipeline is to ensure the entire pipeline, including both the estimator and any preceding transformers, is refitted during the cross-validation process. This is crucial for avoiding data leakage and ensuring a fair evaluation of the model. While options A, B, and D are relevant considerations, option C directly addresses the main purpose of integrating CrossValidator within a Pipeline for consistent refitting across all components during hyperparameter tuning.
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When is it appropriate to include the CrossValidator inside a Pipeline? Choose only ONE best answer.
A
When you want to train models in parallel
B
When there is a risk of data leakage from earlier steps in the pipeline
C
When you want to refit the entire pipeline, including both the estimator and any preceding transformers
D
When there are estimators or transformers in the pipeline
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