"Binary Encoding" in "Decision Tree" / "Random Forest" Algorithms
In general, it &quot;okay&quot; to apply to binary encode high cardinality datasets. In the sense of it will create numerical features that can be learned by a machine learning model.
However there are often better options, such a label encoding, frequency encoding, target encoding, or embeddings.
It is an empirical question which encoding scheme is best for your specific data and model. The best empirical coding scheme can be found through cross validation.