Machine learning drives the process of deciding among alternative candidate splits, i.e., feature information can draw on full structural information for the entire material in the span under consideration.
due to the dynamic programming approach, the features cannot use arbitrarily complex structural configurations: otherwise the dynamic programming chart would have to be split into exponentially many special states.