ensembler | Automated omics-scale protein modeling and simulation setup

The way decision trees and random forest work using splitting logic, I was under the impression that label encoding would not be a problem for these models, as we are anyway going to split the column. For eg: if we have gender as 'male', 'female' and 'other', with label encoding, it becomes 0,1,2 which is interpreted as 0<1<2. But since we are going to split the columns, I thought it didn't matter as it is the same thing whether we are going to split on 'male' or '0'. But when I tried both label and one hot encoding on the dataset, one hot encoding gave better accuracy and precision. Can you kindly share your thoughts.