# does random forest require more trees to be built if # rows increase in train data

I am building a randoForest model on some data. To be able to tune the model faster, I was working with 10% sample. I have tuned it now and now I want to build the model on the whole (100% data).

I am wondering, if I will have to increase the number of trees now that I am building the model on more training data points? Please let me know.

If you train a decision tree directly, there are certain hyperparameters you will want to change. For instance, in sklearn, you will want to double hyperparameters like min_samples_split or min_samples_leaf because in each node you'll have double the observations.