The main features of Bagged Trees are as follows:
1. Reduces variance by averaging the ensemble’s results.
2. The resulting model uses the entire feature space when considering node splits.
3. It allows the trees to grow without pruning, reducing the tree-depth sizes which result in high variance but lower bias, which can help improve the prediction power.