How to tackle Time-series Classification with a large number of categorical variables/attributes ( >100) with high cardinality? I'm open to discussing other ways as well.

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I am predicting whether the particular event would occur or not in the next n-timeframes given the categorical variables with high cardinality. Please let me know if there is anything that we can do to tackle this problem.

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