XGBoost parameter tuning regularization parameters on training set - why?

@laurence70 wrote:

This is an old post so I would like to ask a question here if people have some insight.

Why is tuning the parameter ‘gamma’ (section 3) based upon performance of model on the training set a good idea? Surely you want to evaluate based upon minimizing the difference between training and test set accuracy? Surely tuning regularization parameters on training set will only be a recipe for overfitting disaster?

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