Readme example doesn't work

[azev77]

julia> using MLJTime

julia> # load data
       X, y = ts_dataset("Chinatown");

julia> # split data into training and test set
       train, test = partition(eachindex(y), 0.7, shuffle=true, rng=1234); #70:30 split

julia> X_train, y_train = X[train], y[train];

julia> X_test, y_test = X[test], y[test];

julia> # train model
       model = TimeSeriesForestClassifier(n_trees=3)
TimeSeriesForestClassifier(
    n_trees = 3,
    random_state = nothing,
    min_interval = 3,
    max_depth = -1,
    min_samples_leaf = 1,
    min_samples_split = 2,
    min_purity_increase = 0.0,
    n_subfeatures = 0,
    post_prune = false,
    merge_purity_threshold = 1.0,
    pdf_smoothing = 0.0,
    display_depth = 5) @784

julia> mach = machine(model, X_train, y_train)
Machine{TimeSeriesForestClassifier} @035 trained 0 times.
  args: 
    1:  Source @887 ⏎ `ScientificTypes.Table{AbstractArray{ScientificTypes.Continuous,1}}`
    2:  Source @175 ⏎ `AbstractArray{ScientificTypes.Multiclass{2},1}`

julia> fit!(mach)
[ Info: Training Machine{TimeSeriesForestClassifier} @035.
┌ Error: Problem fitting the machine Machine{TimeSeriesForestClassifier} @035, possibly because an upstream node in a learning network is providing data of incompatible scitype. 
└ @ MLJBase ~/.julia/packages/MLJBase/Ov46j/src/machines.jl:422
[ Info: Running type checks... 
[ Info: Type checks okay. 
ERROR: MethodError: no method matching TimeSeriesForestClassifier(::TimeSeriesForestClassifier, ::IndexedTables.IndexedTable{StructArrays.StructArray{NTuple{24,Float64},1,NTuple{24,Array{Float64,1}},Int64}}, ::Array{UInt32,1})
Closest candidates are:
  TimeSeriesForestClassifier(::Any, ::Array, ::Array) at /Users/AZevelev/.julia/packages/MLJTime/61x0z/src/interval_based_forest.jl:12
Stacktrace:
 [1] fit_only!(::MLJBase.Machine{TimeSeriesForestClassifier}; rows::Nothing, verbosity::Int64, force::Bool) at /Users/AZevelev/.julia/packages/MLJBase/Ov46j/src/machines.jl:433
 [2] fit_only! at /Users/AZevelev/.julia/packages/MLJBase/Ov46j/src/machines.jl:386 [inlined]
 [3] #fit!#85 at /Users/AZevelev/.julia/packages/MLJBase/Ov46j/src/machines.jl:478 [inlined]
 [4] fit!(::MLJBase.Machine{TimeSeriesForestClassifier}) at /Users/AZevelev/.julia/packages/MLJBase/Ov46j/src/machines.jl:476
 [5] top-level scope at none:1

julia> # make predictions
       y_pred = predict_mod(mach, X_test)
ERROR: UndefVarError: predict_mod not defined
Stacktrace:
 [1] top-level scope at none:1

julia> 

[azev77]

It works if you replace: mach = machine(model, X_train, y_train) With: mach = machine(model, matrix(X[train]), y[train])

[azev77]

https://github.com/alan-turing-institute/MLJTime.jl/pull/12

[aa25desh]

Thank you very much:)