Merge pull request #162 from JuliaAI/dev

For a 0.10.1 release

Author: ablaom

.github/workflows/ci.yml

@@ -24,12 +24,12 @@ jobs:
         arch:
           - x64
     steps:
-      - uses: actions/checkout@v2
-      - uses: julia-actions/setup-julia@v1
+      - uses: actions/checkout@v4
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.version }}
           arch: ${{ matrix.arch }}
-      - uses: actions/cache@v1
+      - uses: julia-actions/cache@v2
         env:
           cache-name: cache-artifacts
         with:
@@ -43,6 +43,7 @@ jobs:
       - uses: julia-actions/julia-runtest@v1
         env:
           RUN_COMPARISONS: "false"
+          R_HOME: "*"
       - uses: julia-actions/julia-processcoverage@v1
       - uses: codecov/codecov-action@v1
         with:
@@ -51,8 +52,8 @@ jobs:
     name: Documentation
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v2
-      - uses: julia-actions/setup-julia@v1
+      - uses: actions/checkout@v4
+      - uses: julia-actions/setup-julia@v2
         with:
           version: '1'
       - run: |

Project.toml

@@ -1,7 +1,7 @@
 name = "MLJLinearModels"
 uuid = "6ee0df7b-362f-4a72-a706-9e79364fb692"
 authors = ["Thibaut Lienart <[email protected]>"]
-version = "0.10.0"
+version = "0.10.1"
 
 [deps]
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"

docs/src/quickstart.md

@@ -155,12 +155,12 @@ Which, in my case, gives `setosa`, `setosa` (correct in both cases).
 
 Depending on your data you may want to customize the default solver associated with your model. Since this package uses [Optim](https://julianlsolvers.github.io/Optim.jl/stable/) behind the scene, we can interact directly with this package.
 
-For instance, you may need to be more stringent about the convergence criterion of the LBFGS solver. This can be done by changing the general Optim `f_tol` parameter which defaults to ``10^{-4}``:
+For instance, you may need to be more stringent about the convergence criterion of the LBFGS solver. This can be done by changing the general Optim `f_reltol` parameter which defaults to ``10^{-4}``:
 
 ```julia
 import Optim
 
-new_optim_options = Optim.Options(f_tol=1e-6)
+new_optim_options = Optim.Options(f_reltol=1e-6)
 mdl = MultinomialClassifier(solver=LBFGS(optim_options=new_optim_options))
 mach = machine(mdl, X, y)
 fit!(mach)

src/fit/solvers.jl

@@ -57,7 +57,7 @@ solver = MLJLinearModels.Newton(
 ```
 """
 @with_kw struct Newton{O,S} <: Solver
-    optim_options::O = Optim.Options(f_tol=1e-4)
+    optim_options::O = Optim.Options(f_reltol=1e-4)
     newton_options::S = (; )
 end
 
@@ -84,7 +84,7 @@ solver = MLJLinearModels.NewtonCG(
 ```
 """
 @with_kw struct NewtonCG{O,S} <: Solver
-    optim_options::O = Optim.Options(f_tol=1e-4)
+    optim_options::O = Optim.Options(f_reltol=1e-4)
     newtoncg_options::S = (; )
 end
 
@@ -107,7 +107,7 @@ solver = MLJLinearModels.LBFGS(
 ```
 """
 @with_kw struct LBFGS{O,S} <: Solver
-    optim_options::O = Optim.Options(f_tol=1e-4)
+    optim_options::O = Optim.Options(f_reltol=1e-4)
     lbfgs_options::S = (; )
 end