How to tune the parameters of a VotingClassifier or VotingRegressor in scikit-learn?

I am working on an ensemble learning project, and I am trying to use a voting classifier or voting regression to combine the predictions of multiple models. However, I’m having trouble finding the optimal parameters for my voting classifier and regression model.

Here is a simplified version of my code:

I would like to tune the parameters of my VotingClassifier to achieve better performance. Specifically, I am interested in tuning the hyperparameters of my individual models as well as the voting parameter. Can someone help me with this?

Thanks in advance!

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