fix some mistakes

Author: ablaom

src/fit_update.jl

@@ -44,10 +44,8 @@ LearnAPI.jl does not guarantee such signatures are actually implemented.
 $(DOC_DATA_INTERFACE(:fit))
 
 """
-fit(algorithm, data; kwargs...) =
-    fit(algorithm; kwargs...)
-fit(algorithm, data1, datas...; kwargs...) =
-    fit(algorithm, (data1, datas...); kwargs...)
+function fit end
+
 
 # # UPDATE AND COUSINS
 
@@ -88,7 +86,7 @@ Implementation is optional. The signature must include
 See also [`LearnAPI.clone`](@ref)
 
 """
-update(model, data1, datas...; kwargs...) = update(model, (data1, datas...); kwargs...)
+function update end
 
 """
     update_observations(model, new_data; verbosity=1, parameter_replacements...)
@@ -124,8 +122,7 @@ Implementation is optional. The signature must include
 See also [`LearnAPI.clone`](@ref).
 
 """
-update_observations(algorithm, data1, datas...; kwargs...) =
-    update_observations(algorithm, (data1, datas...); kwargs...)
+function update_observations end
 
 """
     update_features(model, new_data; verbosity=1, parameter_replacements...)
@@ -151,5 +148,4 @@ Implementation is optional. The signature must include
 See also [`LearnAPI.clone`](@ref).
 
 """
-update_features(algorithm, data1, datas...; kwargs...) =
-    update_features(algorithm, (data1, datas...); kwargs...)
+function update_features end

src/predict_transform.jl

@@ -166,8 +166,8 @@ $(DOC_MUTATION(:transform))
 $(DOC_DATA_INTERFACE(:transform))
 
 """
-transform(model, data1, data2, datas...; kwargs...) =
-    transform(model, (data1, data2, datas...); kwargs...) # automatic slurping
+function transform end
+
 
 """
     inverse_transform(model, data)

test/patterns/ensembling.jl

@@ -163,7 +163,7 @@ LearnAPI.strip(model::EnsembleFitted) = EnsembleFitted(
 # convenience method:
 LearnAPI.fit(algorithm::Ensemble, X, y, extras...; kwargs...) =
     fit(algorithm, (X, y, extras...); kwargs...)
-LearnAPI.update(algorithm::Ensemble, X, y, extras...; kwargs...) =
+LearnAPI.update(algorithm::EnsembleFitted, X, y, extras...; kwargs...) =
     update(algorithm, (X, y, extras...); kwargs...)
 
 

test/patterns/static_algorithms.jl

@@ -56,7 +56,6 @@ end
     X = DataFrames.DataFrame(rand(3, 4), [:x, :y, :z, :w])
     model = fit(algorithm) # no data arguments!
     # if provided, data is ignored:
-    @test fit(algorithm, "junk")[] == model[]
     @test LearnAPI.algorithm(model) == algorithm
     W = transform(model, X)
     @test W == DataFrames.DataFrame(Tables.matrix(X)[:,[1,4]], [:x, :w])