Hello everyone,

I am teaching a course using Scikit-Learn, and I wanted to translate my materials to MLJ (for a possible future ), but I am having many problems. I am using MLJ#dev.

First, I have a dataframe with only 4 attributes, all of them are Multiclass and OrderedFactor. I am trying to apply a DecisionTreeClasifier, that it should be use them as it is said with

And the types are rights, I think:

```
println(ScientificTypes.scitype(input_test))
```

gives me:

```
Table{Union{AbstractArray{Multiclass{6},1}, AbstractArray{Multiclass{5},1}, AbstractArray{OrderedFactor{4},1}}}
```

and target_test is from type:

```
AbstractArray{Multiclass{2},1}
```

So, I suppose I can apply it.

However, when I do

```
march = machine(tree, input_test, target_test)
```

It gives me:

```
â”Ś Warning: The scitype of `X`, in `machine(model, X, ...)` is incompatible with `model=DecisionTreeClassifier @140`:
â”‚ scitype(X) = Table{Union{AbstractArray{Multiclass{6},1}, AbstractArray{Multiclass{5},1}, AbstractArray{OrderedFactor{4},1}}}
â”‚ input_scitype(model) = Table{var"#s45"} where var"#s45"<:Union{AbstractArray{var"#s13",1} where var"#s13"<:Continuous, AbstractArray{var"#s13",1} where var"#s13"<:Count, AbstractArray{var"#s13",1} where var"#s13"<:OrderedFactor}.
```

Which could be the reason?

The evaluate! is working with cross_entropy. However, I am not sure it is working well for the previous warning message.