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CompatHelper: bump compat for MLJBase to 1, (keep existing compat) #56

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4 changes: 2 additions & 2 deletions Project.toml
Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
name = "SIRUS"
uuid = "cdeec39e-fb35-4959-aadb-a1dd5dede958"
authors = ["Rik Huijzer <github@huijzer.xyz>"]
version = "1.3.2"
version = "1.3.3"

[deps]
AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"
Expand All @@ -20,7 +20,7 @@ Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
AbstractTrees = "0.3, 0.4"
CategoricalArrays = "0.10"
InlineStrings = "1"
MLJBase = "0.21"
MLJBase = "0.21, 1"
MLJLinearModels = "0.8, 0.9"
MLJModelInterface = "1.4"
OrderedCollections = "1.6.2"
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2 changes: 1 addition & 1 deletion docs/Project.toml
Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@ Documenter = "0.27"
EvoTrees = "0.16"
LiveServer = "1"
MLJ = "0.19"
MLJBase = "0.21"
MLJBase = "0.21, 1"
MLJDecisionTreeInterface = "0.4"
PlutoStaticHTML = "6"
PlutoUI = "0.7"
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4 changes: 3 additions & 1 deletion test/Project.toml
Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@ MLJTestInterface = "72560011-54dd-4dc2-94f3-c5de45b75ecd"
MLJXGBoostInterface = "54119dfa-1dab-4055-a167-80440f4f7a91"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
StatisticalMeasures = "a19d573c-0a75-4610-95b3-7071388c7541"
Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
Expand All @@ -23,10 +24,11 @@ DataDeps = "0.7"
DataFrames = "1.3"
DecisionTree = "0.12"
MLDatasets = "0.7"
MLJBase = "0.21"
MLJBase = "1"
MLJDecisionTreeInterface = "0.4"
MLJLinearModels = "0.9"
MLJTestInterface = "0.2"
MLJXGBoostInterface = "0.3.8"
StableRNGs = "1"
StatisticalMeasures = "0.1"
Tables = "1.7"
7 changes: 4 additions & 3 deletions test/preliminaries.jl
Original file line number Diff line number Diff line change
Expand Up @@ -27,23 +27,24 @@ using MLJBase:
CV,
MLJBase,
PerformanceEvaluation,
accuracy,
auc,
evaluate,
mode,
fit!,
machine,
make_blobs,
make_moons,
make_regression,
rsq,
predict
using MLJDecisionTreeInterface: DecisionTreeClassifier, DecisionTreeRegressor
using MLJLinearModels: LogisticClassifier, LinearRegressor, MultinomialClassifier
using MLJTestInterface: MLJTestInterface
using MLJXGBoostInterface: XGBoostClassifier, XGBoostRegressor
using Random: shuffle, seed!
using StableRNGs: StableRNG
using StatisticalMeasures:
accuracy,
auc,
rsq
using SIRUS
using Statistics: mean, var
using Tables: Tables
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