Update src/encoders/missingness_encoding/interface_mlj.jl

Co-authored-by: Anthony Blaom, PhD <[email protected]>

Author: EssamWisam

src/encoders/missingness_encoding/interface_mlj.jl

@@ -103,7 +103,7 @@ Train the machine using `fit!(mach, rows=...)`.
 - `features=[]`: A list of names of categorical features given as symbols to exclude or include from encoding
 - `ignore=true`: Whether to exclude or includes the features given in `features`
 - `ordered_factor=false`: Whether to encode `OrderedFactor` or ignore them
-- `label_for_missing=Dict{<:Type, <:Any}()= Dict( AbstractString => "missing", Char => 'm', )`: A
+- `label_for_missing::Dict{<:Type, <:Any}()= Dict( AbstractString => "missing", Char => 'm', )`: A
 dictionary where the possible values for keys are the types in `Union{Char, AbstractString, Number}` and where each value
 signifies the new level to map into given a column raw super type. By default, if the raw type of the column subtypes `AbstractString`
 then missing values will be replaced with `"missing"` and if the raw type subtypes `Char` then the new value is `'m'`