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For a 1.9.6 release #196

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merged 5 commits into from
Mar 22, 2024
Merged

For a 1.9.6 release #196

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87d49ba
fix link
ablaom Feb 23, 2024
3e36cc7
fix link
ablaom Feb 23, 2024
d99077b
tweak fit_data_scitype fallback to resolve #170
ablaom Mar 22, 2024
12f588e
bump 1.9.6
ablaom Mar 22, 2024
5ac60f3
Merge pull request #195 from JuliaAI/class-weights-fit-data-scitype
ablaom Mar 22, 2024
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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 = "1.9.5"
version = "1.9.6"

[deps]
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
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4 changes: 2 additions & 2 deletions README.md
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Expand Up @@ -9,11 +9,11 @@ machine learning models into
| :-----------: | :------: |
| [![Build Status](https://github.com/JuliaAI/MLJModelInterface.jl/workflows/CI/badge.svg)](https://github.com/JuliaAI/MLJModelInterface.jl/actions) | [![codecov.io](http://codecov.io/github/JuliaAI/MLJModelInterface.jl/coverage.svg?branch=master)](http://codecov.io/github/JuliaAI/MLJModelInterface.jl?branch=master) |

[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://juliaai.github.io/MLJModelInterface.jl/stable/)
[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://juliaai.github.io/MLJModelInterface.jl/dev/)


[MLJ](https://alan-turing-institute.github.io/MLJ.jl/dev/) is a framework for evaluating,
combining and optimizing machine learning models in Julia. A third party package wanting
to integrate their machine learning models into MLJ must import the module
`MLJModelInterface` defined in this package, as described in the
[documentation]((https://juliaai.github.io/MLJModelInterface.jl/stable/).
[documentation](https://juliaai.github.io/MLJModelInterface.jl/dev/).
2 changes: 1 addition & 1 deletion src/model_traits.jl
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Expand Up @@ -59,7 +59,7 @@ function supervised_fit_data_scitype(M)
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 = Any
return Union{ret, Tuple{I, T, W}}
end
return ret
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