The input scitypes for trees are incorrect

[ablaom]

From here:

    input_scitype    = MMI.Table(MMI.Missing, MMI.Known),           # also ok: MMI.Table(Union{MMI.Missing, MMI.Known}),

What is written in the comment is correct. What is actually used is not:

julia> X = (; x=[missing, 1, 2])
(x = Union{Missing, Int64}[missing, 1, 2],)

julia> scitype(X) <: Table(Missing, Known)
false

julia> scitype(X) <: Table(Union{Missing, Known})
true

For more on the Table scitype constructor, see here.

All the tree scitypes need changing.

Sorry that I did not pick this up in my review.

[sylvaticus]

Thanks, corrected in commit 709b857

By the way, supporting missing predictors makes much slower the DecisionTree algorithm. You may want to try to impute the missing values first with MissingImputator, based on Gaussian Mixture Models.