Hello everyone!

I found an algorithm that allows me to solve the problem of the optimal partition quite(very) quickly. For any type of score (gini index of the target for example) I can find the partition of the input that minimizes it (even on really big datasets). I remind you that in the case of decision trees this optimal partition is not always reached because the algorithm is greedy.

Since I’m not a data-scientist, but rather a combinatorial optimization specialist, I’d like to know if it’s really a discovery or it’s already been done, for example in decision trees implementations.