Are there cyclic decision trees? Usual decision trees are directed acyclic graphs. Are there generalizations of decision trees that contain cycles analogously to recurrent neural networks? If such trees exist, can they be applied to sequences of variable length? I could not find information about such trees. Or their existence is impossible of infeasible?
The goal of decision trees is to partition the feature space into successively smaller regions where each region is best characterized by a single label or value. Adding cyclical components would not help accomplish the goal, it would unnecessarily repeat the modeling fitting for a given region.