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The cross-validation function cv.glmnet, for regularized regression, does not seem to allow for separate transformation/preprocessing of training and validation datasets. As full dataset transformation may lead to data leakage, how can I work around this?

Related question: Does the standardization by glmnet (which is standard, but can be turned off) separate training and validation data?

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  • $\begingroup$ Another related question: if standardization through glmnet does separate data correctly, how would I rewrite it to only center (so no scaling)? $\endgroup$ Commented Oct 30 at 15:24

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