Hi all, got a quick question. Why does ml forecast cross validation take much longer when I fit a random forest regressor compared to xgboost regressor? Xgboost took about 30 seconds for my data but random forest took about 12 mins. Is there a way to speed it up?

hey @Rachel Yee! XGBoost is generally faster due to the underlying gradient calculation. You could reduce the complexity of the hyperparameters of the random forest model, reducing

max_depth

, and

n_estimators

.