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Upgrading Julia LTS version to 1.10 in CI job #164

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d35853d
Upgrading Julia LTS version to `1.10` in CI job
pebeto Nov 6, 2025
3902a50
Update .github/workflows/ci.yml
pebeto Nov 6, 2025
6b28265
Update .github/workflows/documentation.yml
pebeto Nov 6, 2025
c0ce30a
Fixing package dependencies to work with Julia LTS
pebeto Nov 6, 2025
13afbb4
Fixing documentation generation
pebeto Nov 6, 2025
da37eb2
Adding setup R step in CI
pebeto Nov 6, 2025
729acc8
Removing test suite `Project.toml` in favor to root definition
pebeto Nov 6, 2025
f139fa5
Explicitly set `R_HOME` env var in CI pipeline
pebeto Nov 6, 2025
7449761
Rollback to use `R_HOME="*"` instead of installing it manually
pebeto Nov 6, 2025
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3 changes: 1 addition & 2 deletions .github/workflows/ci.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,7 @@ jobs:
fail-fast: false
matrix:
version:
- '1.6'
- 'lts'
- '1'
os:
- ubuntu-latest
Expand All @@ -42,7 +42,6 @@ jobs:
- uses: julia-actions/julia-buildpkg@v1
- uses: julia-actions/julia-runtest@v1
env:
RUN_COMPARISONS: "false"
R_HOME: "*"
- uses: julia-actions/julia-processcoverage@v1
- uses: codecov/codecov-action@v1
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2 changes: 1 addition & 1 deletion .github/workflows/documentation.yml
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Expand Up @@ -14,7 +14,7 @@ jobs:
- uses: actions/checkout@v2
- uses: julia-actions/setup-julia@latest
with:
version: '1.6'
version: 'lts'
- name: Install dependencies
run: julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()'
- name: Build and deploy
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36 changes: 28 additions & 8 deletions Project.toml
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
name = "MLJLinearModels"
uuid = "6ee0df7b-362f-4a72-a706-9e79364fb692"
authors = ["Thibaut Lienart <tlienart@me.com>"]
version = "0.10.1"
authors = ["Thibaut Lienart <tlienart@me.com>"]

[deps]
DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
Expand All @@ -13,10 +13,30 @@ Optim = "429524aa-4258-5aef-a3af-852621145aeb"
Parameters = "d96e819e-fc66-5662-9728-84c9c7592b0a"

[compat]
DocStringExtensions = "0.8, 0.9"
IterativeSolvers = "0.8, 0.9"
LinearMaps = "2.6, 3.2"
MLJModelInterface = "1.4"
Optim = "0.20, 0.21, 1"
Parameters = "0.12"
julia = "1.6, 1"
DocStringExtensions = "0.9.5"
IterativeSolvers = "0.9.4"
LinearMaps = "3.11.4"
MLJModelInterface = "1.12.0"
Optim = "1.13.2"
Parameters = "0.12.3"
julia = "1.10"

[extras]
CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab"
Downloads = "f43a241f-c20a-4ad4-852c-f6b1247861c6"
ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
MLJ = "add582a8-e3ab-11e8-2d5e-e98b27df1bc7"
MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
Optim = "429524aa-4258-5aef-a3af-852621145aeb"
PyCall = "438e738f-606a-5dbb-bf0a-cddfbfd45ab0"
RCall = "6f49c342-dc21-5d91-9882-a32aef131414"
RDatasets = "ce6b1742-4840-55fa-b093-852dadbb1d8b"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

[targets]
test = ["CSV", "DataFrames", "DelimitedFiles", "Downloads", "ForwardDiff", "LinearAlgebra", "MLJ", "MLJBase", "Optim", "PyCall", "RCall", "RDatasets", "Random", "StableRNGs", "Test"]
14 changes: 13 additions & 1 deletion docs/Project.toml
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@@ -1,5 +1,17 @@
[deps]
DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
IterativeSolvers = "42fd0dbc-a981-5370-80f2-aaf504508153"
LinearMaps = "7a12625a-238d-50fd-b39a-03d52299707e"
MLJModelInterface = "e80e1ace-859a-464e-9ed9-23947d8ae3ea"
Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
Optim = "429524aa-4258-5aef-a3af-852621145aeb"
Parameters = "d96e819e-fc66-5662-9728-84c9c7592b0a"

[compat]
Documenter = "^0.24"
DocStringExtensions = "0.9.5"
IterativeSolvers = "0.9.4"
LinearMaps = "3.11.4"
MLJModelInterface = "1.12.0"
Documenter = "1.15.0"
Optim = "1.13.2"
Parameters = "0.12.3"
4 changes: 3 additions & 1 deletion docs/make.jl
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@@ -1,3 +1,4 @@
push!(LOAD_PATH, "../src/")
using Documenter, MLJLinearModels

makedocs(
Expand All @@ -13,7 +14,8 @@ makedocs(
"Models" => "models.md",
"Solvers" => "solvers.md",
"API" => "api.md"
]
],
warnonly=[:cross_references, :missing_docs],
)

deploydocs(
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26 changes: 0 additions & 26 deletions test/Project.toml
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4 changes: 2 additions & 2 deletions test/interface/fitpredict.jl
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Expand Up @@ -37,7 +37,7 @@ end
ŷ = MLJBase.predict(lr, fr, Xt)
ŷ = MLJBase.mode.(ŷ)

mcr = MLJBase.misclassification_rate(ŷ, yc)
mcr = MLJ.misclassification_rate(ŷ, yc)
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@ablaom ablaom Nov 6, 2025

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I doubt you really need MLJ here. The metrics used to be defined in MLJBase, but now they are provided by StatisticalMeasures.jl

@test mcr ≤ 0.2
end

Expand All @@ -62,7 +62,7 @@ end
ŷ = MLJBase.predict(mc, fr, Xt)
ŷ = MLJBase.mode.(ŷ)

mcr = MLJBase.misclassification_rate(ŷ, yc)
mcr = MLJ.misclassification_rate(ŷ, yc)
@test mcr ≤ 0.3
end

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