Lasso with Categorical Variables

Asked Jun 25 '21 at 00:50

Active Jun 25 '21 at 02:11

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I am running a lasso model to predict a continuous variable, and I have continuous and categorical inputs.

In terms of centering and scaling - is it correct that this should only be applied to continuous variables?
Also, in terms of the dummy variables step, can this be ignored for the categorical? It just doesn't make sense when it comes to scoring.
- For example, if the training set has a category called Cats, that has levels A-Z, this would create a column for A-Z. But if my scoring set is missing one of these levels then it will fall over. Looking for some guidance.

edited Jun 25 '21 at 02:11

Sycorax

asked Jun 25 '21 at 00:50

Mathew Lionnet

I mean an independent predictor variable, the target variable is continuous. – Mathew Lionnet Jun 25 '21 at 01:46
Does this answer your question? Ridge\Lasso -- Standardization of dummy indicators That covers the centering/scaling. Group lasso provides a way to handle all levels of a multi-level categorical predictor, although details might depend on your particular data set and purpose for modeling. – EdM Jun 25 '21 at 02:29
Yes, that kind of helps, thanks! – Mathew Lionnet Jun 25 '21 at 03:10

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