bump [compat] LearnAPI = "1" and address breakages

Author: anthony

Project.toml

@@ -46,7 +46,7 @@ ComputationalResources = "0.3"
 DelimitedFiles = "1"
 Distributions = "0.25.3"
 InvertedIndices = "1"
-LearnAPI = "0.1"
+LearnAPI = "1"
 MLJModelInterface = "1.11"
 Missings = "0.4, 1"
 OrderedCollections = "1.1"

src/resampling.jl

@@ -1,4 +1,4 @@
- # TYPE ALIASES
+# TYPE ALIASES
 
 const AbstractRow = Union{AbstractVector{<:Integer}, Colon}
 const TrainTestPair = Tuple{AbstractRow,AbstractRow}
@@ -873,7 +873,7 @@ function _check_measure(measure, operation, model, y)
     end
 
     model isa Deterministic &&
-        StatisticalMeasuresBase.kind_of_proxy(measure) != LearnAPI.LiteralTarget() &&
+        StatisticalMeasuresBase.kind_of_proxy(measure) != LearnAPI.Point() &&
         throw(ERR_MEASURES_DETERMINISTIC(measure))
 
     return true
@@ -962,7 +962,7 @@ function _actual_operations(operation::Nothing,
         # trait. But it's values are instances of LearnAPI.KindOfProxy, instead of
         # symbols:
         #
-        # `LearnAPI.LiteralTarget()` ~ `:deterministic` (`model isa Deterministic`)
+        # `LearnAPI.Point()`        ~ `:deterministic` (`model isa Deterministic`)
         # `LearnAPI.Distribution()` ~ `:probabilistic` (`model isa Deterministic`)
         #
         kind_of_proxy = StatisticalMeasuresBase.kind_of_proxy(m)
@@ -983,7 +983,7 @@ function _actual_operations(operation::Nothing,
         if MLJBase.prediction_type(model) === :probabilistic
             if kind_of_proxy === LearnAPI.Distribution()
                 return predict
-            elseif kind_of_proxy === LearnAPI.LiteralTarget()
+            elseif kind_of_proxy === LearnAPI.Point()
                 if observation_scitype <: Union{Missing,Finite}
                     return predict_mode
                 elseif observation_scitype <:Union{Missing,Infinite}
@@ -997,7 +997,7 @@ function _actual_operations(operation::Nothing,
         elseif MLJBase.prediction_type(model) === :deterministic
             if kind_of_proxy === LearnAPI.Distribution()
                 throw(err_incompatible_prediction_types(model, m))
-            elseif kind_of_proxy === LearnAPI.LiteralTarget()
+            elseif kind_of_proxy === LearnAPI.Point()
                 return predict
             else
                 throw(err_ambiguous_operation(model, m))

src/utilities.jl

@@ -475,11 +475,9 @@ generate_name!(model, existing_names; kwargs...) =
 
 *Private method.*
 
-Tries to infer the per-observation scitype from the scitype of `S`, when `S` is
-known to be the scitype of some container with multiple observations; here we
-view the scitype for one row of a table to be the scitype of the row converted
-to a vector. Return `Unknown` if unable to draw reliable inferrence.
-
+Tries to infer the per-observation scitype from the scitype of `S`, when `S` is known to
+be the scitype of some container with multiple observations. Return `Unknown` if unable to
+draw reliable inferrence.
 
 The observation scitype for a table is here understood as the scitype of a row
 converted to a vector.