For a 0.17 release

.github/workflows/ci.yml

@@ -42,6 +42,6 @@ jobs:
       - uses: julia-actions/julia-buildpkg@v1
       - uses: julia-actions/julia-runtest@v1
       - uses: julia-actions/julia-processcoverage@v1
-      - uses: codecov/codecov-action@v1
+      - uses: codecov/codecov-action@v3
         with:
           file: lcov.info

Project.toml

@@ -1,7 +1,7 @@
 name = "MLJModels"
 uuid = "d491faf4-2d78-11e9-2867-c94bc002c0b7"
 authors = ["Anthony D. Blaom <[email protected]>"]
-version = "0.16.17"
+version = "0.17.0"
 
 [deps]
 CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
@@ -37,7 +37,7 @@ Distributions = "0.25"
 InteractiveUtils = "<0.0.1, 1"
 LinearAlgebra = "<0.0.1, 1"
 Markdown = "<0.0.1, 1"
-MLJModelInterface = "1.4"
+MLJModelInterface = "1.10"
 OrderedCollections = "1.1"
 Parameters = "0.12"
 Pkg = "<0.0.1, 1"

README.md

@@ -1,13 +1,13 @@
 # MLJModels
 
-[![Build Status](https://github.com/alan-turing-institute/MLJModels.jl/workflows/CI/badge.svg)](https://github.com/alan-turing-institute/MLJModels.jl/actions)
+[![Build Status](https://github.com/JuliaAI/MLJModels.jl/workflows/CI/badge.svg)](https://github.com/JuliaAI/MLJModels.jl/actions)
 
 Repository of the "built-in" models available for use in the
-[MLJ](https://github.com/alan-turing-institute/MLJ.jl) MLJ machine
+[MLJ](https://github.com/JuliaAI/MLJ.jl) MLJ machine
 learning framework; and the home of the MLJ model registry.
 
 For instructions on integrating a new model with MLJ visit
-[here](https://alan-turing-institute.github.io/MLJ.jl/dev/adding_models_for_general_use/)
+[here](https://JuliaAI.github.io/MLJ.jl/dev/adding_models_for_general_use/)
 
 
 ### Contents
@@ -19,7 +19,7 @@ For instructions on integrating a new model with MLJ visit
 ## Who is this repo for?
 
 General users of the MLJ machine learning platform should refer to
-[MLJ home page](https://alan-turing-institute.github.io/MLJ.jl/dev/)
+[MLJ home page](https://JuliaAI.github.io/MLJ.jl/dev/)
 for usage and installation instructions. MLJModels is a dependency of
 MLJ that the general user can ignore.
 
@@ -32,7 +32,7 @@ model interfaces, whether they be:
   [`EvoTrees.jl`](https://github.com/Evovest/EvoTrees.jl/blob/master/src/MLJ.jl); or
 
 - implemented in a separate **interface package**, such as
-  [MLJDecisionTreeInterface.jl](https://github.com/alan-turing-institute/MLJDecisionTreeInterface.jl).
+  [MLJDecisionTreeInterface.jl](https://github.com/JuliaAI/MLJDecisionTreeInterface.jl).
 
 It also a place for developers to add models (mostly transformers)
 such as `OneHotEncoder`, that are exported for "built-in" use in
@@ -63,16 +63,16 @@ MLJModels contains:
   models that can be called from MLJ using `@load`. Package developers
   can register new models by implementing the MLJ interface in their
   package and following [these
-  instructions](https://alan-turing-institute.github.io/MLJ.jl/dev/adding_models_for_general_use/).
+  instructions](https://JuliaAI.github.io/MLJ.jl/dev/adding_models_for_general_use/).
 
 
 ## Instructions for updating the MLJ model registry
 
 Generally model registration is performed by administrators. If you
 have an interface you would like registered, open an issue
-[here](https://github.com/alan-turing-institute/MLJ.jl/issues). 
+[here](https://github.com/JuliaAI/MLJ.jl/issues). 
 
 **Administrator instructions.** These are given in the
 `MLJModels.@update` document string. After registering the model, make a PR to MLJ 
-updating [this dictionary of model descriptors](https://github.com/alan-turing-institute/MLJ.jl/blob/dev/docs/ModelDescriptors.toml) 
-to ensure the new models appear in the right places in MLJ's [Model Browser](https://alan-turing-institute.github.io/MLJ.jl/dev/model_browser/#Model-Browser)
+updating [this dictionary of model descriptors](https://github.com/JuliaAI/MLJ.jl/blob/dev/docs/ModelDescriptors.toml) 
+to ensure the new models appear in the right places in MLJ's [Model Browser](https://JuliaAI.github.io/MLJ.jl/dev/model_browser/#Model-Browser)

src/MLJModels.jl

@@ -59,6 +59,11 @@ nonmissing = nonmissingtype
 
 include("utilities.jl")
 
+# load built-in models:
+include("builtins/Constant.jl")
+include("builtins/Transformers.jl")
+include("builtins/ThresholdPredictors.jl")
+
 Handle = NamedTuple{(:name, :pkg), Tuple{String,String}}
 (::Type{Handle})(name,string) = NamedTuple{(:name, :pkg)}((name, string))
 
@@ -79,11 +84,6 @@ include("loading.jl")
 include("registry/src/Registry.jl")
 using .Registry
 
-# load built-in models:
-include("builtins/Constant.jl")
-include("builtins/Transformers.jl")
-include("builtins/ThresholdPredictors.jl")
-
 # finalize:
 include("init.jl")
 

src/builtins/Constant.jl

@@ -99,7 +99,7 @@ metadata_pkg.(
      DeterministicConstantRegressor, DeterministicConstantClassifier),
     name       = "MLJModels",
     uuid       = "d491faf4-2d78-11e9-2867-c94bc002c0b7",
-    url        = "https://github.com/alan-turing-institute/MLJModels.jl",
+    url        = "https://github.com/JuliaAI/MLJModels.jl",
     julia      = true,
     license    = "MIT",
     is_wrapper = false)

src/builtins/ThresholdPredictors.jl

@@ -327,15 +327,9 @@ MMI.package_name(::Type{<:ThresholdUnion}) = "MLJModels"
 MMI.package_uuid(::Type{<:ThresholdUnion}) = ""
 MMI.is_wrapper(::Type{<:ThresholdUnion}) = true
 MMI.package_url(::Type{<:ThresholdUnion}) =
-    "https://github.com/alan-turing-institute/MLJModels.jl"
-
-for New in THRESHOLD_TYPE_EXS
-    New_str = string(New)
-    quote
-        MMI.load_path(::Type{<:$New{M}}) where M = "MLJModels."*$New_str
-    end |> eval
-end
-
+    "https://github.com/JuliaAI/MLJModels.jl"
+MMI.load_path(::Type{<:ThresholdUnion}) = "MLJModels.BinaryThresholdPredictor"
+MMI.constructor(::Type{<:ThresholdUnion}) = BinaryThresholdPredictor
 
 for trait in [:supports_weights,
               :supports_class_weights,