@Rahul Thanks for reporting. Which DecisionTreeClassifier are you using? The one from DecisionTree.jl is not compatible with missing values. It assumes any feature is ordered.
However, I believe the BetaML version does support missing values but there I see there is a bug in the input scitype declaration which would trigger the warning you are seeing. If you ignore the warning you should be fine, assuming that is the packages you are using. It can be loaded with
BetaMLTree = @load DecisionTreeClassifier pkg=BetaML add=true
tree = BetaMLTree()
I’ve posted an issue here to request fixing the scitype.
cc @sylvaticus