TimeSeries with Pycaret - Is a proper Hyperparametertuning (e.g. via Optuna) impossible?

[D3NE3N]

Hello,

I have delved deeper into hyperparameter tuning in pycaret (time series). Currently, it seems that only random_search and grid_search are available as search strategies for time series.

random_search is suboptimal since it is a random (unsystematic) search.

grid_search is also suboptimal because it involves complete (unsystematic) enumeration.

Is there currently any option or workaround for the time series case in Pycaret to perform a proper hyperparameter tuning (e.g., using genetic algorithms which are part of Optuna)?

If it's currently not possible, is there a plan for such a feature (e.g., integration of Optuna into Pycaret for time series forecasting) in the future? If yes, when is this planned?

Pycaret really is a great package. In my opinion, however, it is really sad that this important functionality seems not yet available.