Merge pull request #13 from JuliaAI/arithmetic

Use CategoricalDistributions for UnivariateFinite, instead of MLJBase

Author: ablaom

Project.toml

@@ -1,36 +1,38 @@
 name = "MLJEnsembles"
 uuid = "50ed68f4-41fd-4504-931a-ed422449fee0"
 authors = ["Anthony D. Blaom <anthony.blaom@gmail.com>"]
-version = "0.1.2"
+version = "0.2.0"
 
 [deps]
 CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
+CategoricalDistributions = "af321ab8-2d2e-40a6-b165-3d674595d28e"
 ComputationalResources = "ed09eef8-17a6-5b46-8889-db040fac31e3"
 Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
 MLJModelInterface = "e80e1ace-859a-464e-9ed9-23947d8ae3ea"
 ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-ScientificTypes = "321657f4-b219-11e9-178b-2701a2544e81"
+ScientificTypesBase = "30f210dd-8aff-4c5f-94ba-8e64358c1161"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 
 [compat]
 CategoricalArrays = "0.8, 0.9, 0.10"
+CategoricalDistributions = "0.1.2"
 ComputationalResources = "0.3"
 Distributions = "0.21, 0.22, 0.23, 0.24, 0.25"
-MLJBase = "0.18"
+MLJBase = "0.19"
 MLJModelInterface = "0.4.1, 1.1"
 ProgressMeter = "1.1"
-ScientificTypes = "2"
+ScientificTypesBase = "2,3"
 StatsBase = "0.32, 0.33"
 julia = "1.1"
 
 [extras]
-MLJModels = "d491faf4-2d78-11e9-2867-c94bc002c0b7"
-NearestNeighborModels = "636a865e-7cf4-491e-846c-de09b730eb36"
+Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
+NearestNeighbors = "b8a86587-4115-5ab1-83bc-aa920d37bbce"
 StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["MLJModels", "NearestNeighborModels", "StableRNGs", "Test"]
+test = ["Distances", "NearestNeighbors", "StableRNGs", "Test"]

src/MLJEnsembles.jl

@@ -1,5 +1,21 @@
 module MLJEnsembles
 
+using MLJModelInterface
+import MLJModelInterface: predict, fit
+import MLJBase # still needed for aggregating measures in oob-estimates of error
+using Random
+using CategoricalArrays
+using CategoricalDistributions
+using ComputationalResources
+using Distributed
+import Distributions
+using ProgressMeter
+import StatsBase
+
+export EnsembleModel
+
+const MMI = MLJModelInterface
+
 include("ensembles.jl")
 
 end # module