I have seen many posts online about tuning the random forest hyperparameters with a gridsearch. however, since the random forest creates trees with some randomness, does this have sense? Wouldn't the best parameters just be because of a lucky model?
Let me make an example. I tuned the parameters of an ExtraTreeClassifier, getting very nice results. However, training with the same parameters changing the random state (seed) of the model leads to terrible performance. Am I allowed to think that the model trained works well?