Random Forests

Learning curves are similar

Varying the number of estimators and the max features doesn't affect the learning curves much. You can see below that the learning curves are almost identical, overfitting quickly on the training and improving gradually as the train set size increases.

Larger range in R^2 on validation data

The R^2 on the validation data is more informative: increasing the number of estimators from 10 to 100, and the max features to "sqrt" (square root) gives better results by up to 11 points.