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Validation and Learning Curves with Pipeline or Model Only?

Cross Validated Asked by Odisseo on December 23, 2021

I have a pretty complex Sklearn pipeline including Standardization, PCA, and more.

I created a couple of models and would like to evaluate them with learning and validation curves.

I find myself wondering whether if I should use the entire pipeline object or just the final model for drawing the curves. I presume the former.

One Answer

The correct answer is the former. One should always cross validate with the entire pipeline as even steps such as feature selection have a dependency on the dataset split chosen.

Answered by Odisseo on December 23, 2021

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