What regression tree ensemble methods and what parameters does Matlab actually consider in hyperparameter tuning?
But what is the search space here?
The output in that example only displays Bag and LSBoost as methods. Does it neglect random forests, i.e. subset sampling instead of bootstrapping the input space? Or is bagging here an umbrella term that covers also Random Forests?
Furthermore, the output in the above example only displays NumLearnCycles (tree count), LearnRate (for boosting) and MinLeafSize (obvious). How about treatment of the other CART decision tree algorithm hyperparameters? Are they included as default values - if so, then where to find them?