tweaks

Author: ablaom

examples/bigtest/Project.toml

@@ -5,7 +5,6 @@ EvoTrees = "f6006082-12f8-11e9-0c9c-0d5d367ab1e5"
 InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
 LightGBM = "7acf609c-83a4-11e9-1ffb-b912bcd3b04a"
 MLJ = "add582a8-e3ab-11e8-2d5e-e98b27df1bc7"
-MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
 MLJClusteringInterface = "d354fa79-ed1c-40d4-88ef-b8c7bd1568af"
 MLJDecisionTreeInterface = "c6f25543-311c-4c74-83dc-3ea6d1015661"
 MLJFlux = "094fc8d1-fd35-5302-93ea-dabda2abf845"

examples/bigtest/notebook.jl

@@ -16,7 +16,10 @@ using DataFrames # for displaying tables
 # # Regression
 
 known_problems = models() do model
-    !model.is_pure_julia ||
+    model.package_name in [
+        "ScikitLearn",
+        "LIBSVM",
+    ] ||
     any([
         # https://github.com/lalvim/PartialLeastSquaresRegressor.jl/issues/29
         model.package_name == "PartialLeastSquaresRegressor",
@@ -47,9 +50,11 @@ report1 |> DataFrame
 # # Classification
 
 known_problems = models() do model
-    !model.is_pure_julia ||
-    (name = model.name, package_name = model.package_name) in
-    [
+    model.package_name in [
+        "ScikitLearn",
+        "LIBSVM",
+    ] || (name = model.name, package_name = model.package_name) in [
+
         # https://github.com/JuliaAI/MLJMultivariateStatsInterface.jl/issues/41
         (name = "LDA", package_name = "MultivariateStats"),
         (name = "SubspaceLDA", package_name = "MultivariateStats"),

src/attemptors.jl

@@ -129,7 +129,7 @@ end
 function evaluation(measure, model, resources, data...; throw=false, verbosity=1)
     L = length(resources)
     message = L > 1 ? "[:accelerated_evaluation] " : "[evaluation] "
-    message *=  "Evaluating model performance using with $L resources. "
+    message *=  "Evaluating model performance using $L different resources. "
     attempt(finalize(message, verbosity); throw) do
         es = map(resources) do accel
             evaluate(model, data...;
@@ -206,7 +206,7 @@ function stack_evaluation(
     L = length(resources)
     message = L > 1 ? "[:accelerated_stack_evaluation] " : "[stack_evaluation] "
     message *=  "Evaluating a stack containing model "*
-        "with $L resources. "
+        "with $L different resources. "
     target_scitype = MLJ.target_scitype(model)
     if  AbstractVector{Continuous} <: target_scitype
         models = (knn1=KNNRegressor(K=4),