For a 0.4.1 release

.github/codecov.yml

@@ -0,0 +1,8 @@
+coverage:
+  status:
+    project:
+      default:
+        threshold: 0.5%
+    patch:
+      default:
+        target: 80%

Project.toml

@@ -1,7 +1,7 @@
 name = "MLJDecisionTreeInterface"
 uuid = "c6f25543-311c-4c74-83dc-3ea6d1015661"
 authors = ["Anthony D. Blaom <[email protected]>"]
-version = "0.4.0"
+version = "0.4.1"
 
 [deps]
 CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
@@ -21,7 +21,8 @@ julia = "1.6"
 MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
 MLJTestInterface = "72560011-54dd-4dc2-94f3-c5de45b75ecd"
 StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
+StatisticalMeasures = "a19d573c-0a75-4610-95b3-7071388c7541"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["MLJBase", "MLJTestInterface", "StableRNGs", "Test"]
+test = ["MLJBase", "MLJTestInterface", "StableRNGs", "StatisticalMeasures", "Test"]

README.md

@@ -1,4 +1,4 @@
-# DecisionTree.jl
+# MLJDecisionTreeInterface.jl
 
 Repository implementing the MLJ model interface for 
 [DecisionTree](https://github.com/bensadeghi/DecisionTree.jl) models.

src/MLJDecisionTreeInterface.jl

@@ -15,9 +15,10 @@ const PKG = "MLJDecisionTreeInterface"
 
 struct TreePrinter{T}
     tree::T
+    features::Vector{Symbol}
 end
-(c::TreePrinter)(depth) = DT.print_tree(c.tree, depth)
-(c::TreePrinter)() = DT.print_tree(c.tree, 5)
+(c::TreePrinter)(depth) = DT.print_tree(c.tree, depth, feature_names = c.features)
+(c::TreePrinter)() = DT.print_tree(c.tree, 5, feature_names = c.features)
 
 Base.show(stream::IO, c::TreePrinter) =
     print(stream, "TreePrinter object (call with display depth)")
@@ -71,7 +72,7 @@ function MMI.fit(
     cache  = nothing
     report = (
         classes_seen=classes_seen,
-        print_tree=TreePrinter(tree),
+        print_tree=TreePrinter(tree, features),
         features=features,
     )
     return fitresult, cache, report
@@ -765,6 +766,8 @@ The fields of `fitted_params(mach)` are:
 
 # Report
 
+The fields of `report(mach)` are:
+
 - `features`: the names of the features encountered in training
 
 
@@ -862,6 +865,8 @@ The fields of `fitted_params(mach)` are:
 
 # Report
 
+The fields of `report(mach)` are:
+
 - `features`: the names of the features encountered in training
 
 
@@ -968,6 +973,8 @@ The fields of `fitted_params(mach)` are:
 
 # Report
 
+The fields of `report(mach)` are:
+
 - `features`: the names of the features encountered in training
 
 
@@ -1079,6 +1086,8 @@ The fields of `fitted_params(mach)` are:
 
 # Report
 
+The fields of `report(mach)` are:
+
 - `features`: the names of the features encountered in training
 
 

test/runtests.jl

@@ -6,6 +6,7 @@ using StableRNGs
 using Random
 using Tables
 import MLJTestInterface
+using StatisticalMeasures
 
 # load code to be tested:
 import DecisionTree