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Fix handling weights in supervised fit data scitype #137

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merged 2 commits into from
Jan 28, 2022
Merged

Fix handling weights in supervised fit data scitype #137

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e9d9ea9
fix incorrect definition of supervised_fit_data_scitype re weights
ablaom Jan 27, 2022
c2b4a66
bump 1.3.6
ablaom Jan 27, 2022
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2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
name = "MLJModelInterface"
uuid = "e80e1ace-859a-464e-9ed9-23947d8ae3ea"
authors = ["Thibaut Lienart and Anthony Blaom"]
version = "1.3.5"
version = "1.3.6"

[deps]
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
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6 changes: 3 additions & 3 deletions src/model_traits.jl
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Expand Up @@ -54,10 +54,10 @@ function supervised_fit_data_scitype(M)
T = target_scitype(M)
ret = Tuple{I, T}
if supports_weights(M)
W = AbstractVector{Union{Continuous, Count}} # weight scitype
W = AbstractVector{<:Union{Continuous, Count}} # weight scitype
return Union{ret, Tuple{I, T, W}}
elseif supports_class_weights(M)
W = AbstractDict{Finite, Union{Continuous, Count}}
W = AbstractDict{Finite, <:Union{Continuous, Count}}
return Union{ret, Tuple{I, T, W}}
end
return ret
Expand All @@ -67,7 +67,7 @@ StatTraits.fit_data_scitype(M::Type{<:Unsupervised}) = Tuple{input_scitype(M)}
StatTraits.fit_data_scitype(::Type{<:Static}) = Tuple{}
StatTraits.fit_data_scitype(M::Type{<:Supervised}) = supervised_fit_data_scitype(M)

# In special case of `UnsupervisedAnnotator`, we allow the target
# In special case of `UnsupervisedAnnotator`, we allow the target
# as an optional argument to `fit` (that is ignored) so that the
# `machine` constructor will accept it as a valid argument, which
# then enables *evaluation* of the detector with labeled data:
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