Frédéric LeBlanc

Decision trees as partitioning machines to characterize their generalization properties

Decision trees are popular machine learning models that are simple to build and easy to interpret. Even though algorithms to learn decision trees date back to almost 50 years, key properties affecting their generalization error are still weakly bounded. Hence, we revisit binary decision trees on rea…