#feature-subsampling

Question 1: Single choice

Which option correctly describes the sources of randomness in a random forest?

Bootstrap samples of the training data, with all features considered at every split1
Bootstrap samples of the training data and a random subset of features at each split2
Random feature subsets at each split, with every tree trained on the full training set3
Random initial values for the leaf predictions, refined during training4