Categorical Variable with too many levels for Decision Tree I am trying to build a decision tree but the problem is I have too many levels on one of my categorical variable. The variable is 'source' - It indicates the source website where the user came from. I want to include this variable in my decision tree. How to deal with the many levels?

One tactic is finding quantitative characterizations, or at the very least categorical characterizations with fewer levels, of the original levels. The most obvious is mean encoding, but you can try out anything you can think of: length of URL, top level domain name, etc. Take a look at the URLs and see if any categorization occurs to you.
Another tactic is ensemble modelling. Reducing the number of features can increase the number of levels that a model can usefully incorporate, so if you can find subsets of the features that yield useful results, you can build a model for each subset, and then build an ensemble model.
Keep in mind that the more things you throw at it, the higher the risk of overfitting.
