What strategies would you recommend for managing categorical variables that exhibit high cardinality?

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Anonymous · Accepted Answer

we could use feature engineering to combine two or more features in the
categorical feature. We could ensemble technique by applying algorithms like
random forest or gradient boosting which better handles data with high
cardinality. Another approach is to perform dimensionality reduction

Anonymous · Answer

I think any decision tree approach would be best to handle high cardinal data.
We can use random forest for a relatively interpretable approach otherwise we
can use XGBoost for a more robust and accurate approach.

What strategies would you recommend for managing categorical variables that exhibit high cardinality?

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