Hello Everyone:

I am attempting to run:

```
curve_clf = MLJ.learning_curve(r_clf, feat, targ,
range=r_clf,
resampling=MLJ.Holdout(fraction_train=0.8),
measure=MLJ.cross_entropy)
```

But am encountering the following error:

```
MethodError: no method matching learning_curve(::MLJBase.NumericRange{Int64, MLJBase.Bounded, Symbol}, ::DataFrames.DataFrame, ::CategoricalArrays.CategoricalVector{Float64, UInt32, Float64, CategoricalArrays.CategoricalValue{Float64, UInt32}, Union{}}; rng=NumericRange{Int64,…} @983, resampling=Holdout @695, measure=LogLoss{Float64} @702)
```

The system suggestion is:

```
learning_curve(!Matched::MLJModelInterface.Supervised, ::Any...; resolution, resampling, weights, measures, measure, rows, operation, ranges, range, repeats, acceleration, acceleration_grid, verbosity, rngs, rng_name, check_measure)
```

Any suggestions out there?