HPX allows users to parallel their for-loops. The user can change values of chunk size and prefetching distance with existing execution policies. Some of these policies use machine learning the optimal chunk size and prefetching distance for a given for-loop. However, these machine learning algorithms are classification algorithms so the number of possible outcome is limited. The idea is to use regression algorithms to allow for as many outcomes as needed.