rm some redundant code

Author: ablaom

src/MLJTestIntegration.jl

@@ -10,6 +10,7 @@ using NearestNeighborModels
 import MLJTestInterface
 const MTI = MLJTestInterface
 import MLJTestInterface.attempt
+import MLJTestInterface: make_binary, make_multiclass, make_regression, make_count
 
 include("attemptors.jl")
 include("test.jl")

src/special_cases.jl

@@ -39,56 +39,6 @@ end
 _test(data; ignore=true, kwargs...) = _test([], data; ignore, kwargs...)
 
 
-# # BABY DATA SETS
-
-"""
-    make_binary()
-
-Return data `(X, y)` for the crabs dataset, restricted to the two features `:FL`,
-`:RW`. Target is `Multiclass{2}`.
-
-"""
-function make_binary()
-    data = MLJ.load_crabs()
-    y_, X = unpack(data, ==(:sp), col->col in [:FL, :RW])
-    y = coerce(y_, MLJ.OrderedFactor)
-    return X, y
-end
-
-"""
-    make_multiclass()
-
-Return data `(X, y)` for the unshuffled iris dataset. Target is `Multiclass{3}`.
-
-"""
-make_multiclass() = MLJ.@load_iris
-
-"""
-    make_regression()
-
-Return data `(X, y)` for the Boston dataset, restricted to the two features `:LStat`,
-`:Rm`. Target is `Continuous`.
-
-"""
-function make_regression()
-    data = MLJ.load_boston()
-    y, X = unpack(data, ==(:MedV), col->col in [:LStat, :Rm])
-    return X, y
-end
-
-"""
-    make_count()
-
-Return data `(X, y)` for the Boston dataset, restricted to the two features `:LStat`,
-`:Rm`, with the `Continuous` target converted to `Count` (integer).
-
-"""
-function make_count()
-    X, y_ = make_regression()
-    y = map(η -> round(Int, η), y_)
-    return X, y
-end
-
 
 # # SINGLE TARGET CLASSIFICATION