Package evaluation of DecisionTree on Julia 1.13.0-DEV.985 (9c94e7ae32*) started at 2025-08-14T12:12:12.710 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 9.9s ################################################################################ # Installation # Installing DecisionTree... Resolving package versions... Updating `~/.julia/environments/v1.13/Project.toml` [7806a523] + DecisionTree v0.12.4 Updating `~/.julia/environments/v1.13/Manifest.toml` [1520ce14] + AbstractTrees v0.4.5 [7806a523] + DecisionTree v0.12.4 [8bb1440f] + DelimitedFiles v1.9.1 [6e75b9c4] + ScikitLearnBase v0.5.0 [10745b16] + Statistics v1.11.1 [56f22d72] + Artifacts v1.11.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.13.0 [a63ad114] + Mmap v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v0.7.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [4536629a] + OpenBLAS_jll v0.3.29+0 [8e850b90] + libblastrampoline_jll v5.13.1+0 Installation completed after 1.18s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 19.78s ################################################################################ # Testing # Testing DecisionTree Status `/tmp/jl_jROcZG/Project.toml` [1520ce14] AbstractTrees v0.4.5 [7806a523] DecisionTree v0.12.4 [8bb1440f] DelimitedFiles v1.9.1 [6e75b9c4] ScikitLearnBase v0.5.0 [860ef19b] StableRNGs v1.0.3 [10745b16] Statistics v1.11.1 [37e2e46d] LinearAlgebra v1.13.0 [9a3f8284] Random v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_jROcZG/Manifest.toml` [1520ce14] AbstractTrees v0.4.5 [7806a523] DecisionTree v0.12.4 [8bb1440f] DelimitedFiles v1.9.1 [6e75b9c4] ScikitLearnBase v0.5.0 [860ef19b] StableRNGs v1.0.3 [10745b16] Statistics v1.11.1 [56f22d72] Artifacts v1.11.0 [2a0f44e3] Base64 v1.11.0 [b77e0a4c] InteractiveUtils v1.11.0 [ac6e5ff7] JuliaSyntaxHighlighting v1.12.0 [8f399da3] Libdl v1.11.0 [37e2e46d] LinearAlgebra v1.13.0 [56ddb016] Logging v1.11.0 [d6f4376e] Markdown v1.11.0 [a63ad114] Mmap v1.11.0 [9a3f8284] Random v1.11.0 [ea8e919c] SHA v0.7.0 [9e88b42a] Serialization v1.11.0 [f489334b] StyledStrings v1.11.0 [8dfed614] Test v1.11.0 [e66e0078] CompilerSupportLibraries_jll v1.3.0+1 [4536629a] OpenBLAS_jll v0.3.29+0 [8e850b90] libblastrampoline_jll v5.13.1+0 Testing Running tests... Julia version: 1.13.0-DEV.985 TEST: classification/random.jl Feature 1 < 0.4006 ? ├─ Feature 2 < 0.5183 ? ├─ Feature 5 < 0.4131 ? ├─ 0 : 62/73 └─ -1 : 107/121 └─ Feature 5 < 0.7296 ? ├─ -1 : 133/140 └─ -1 : 27/54 └─ Feature 5 < 0.5163 ? ├─ Feature 2 < 0.6788 ? ├─ 0 : 204/223 └─ 0 : 70/91 └─ Feature 2 < 0.4592 ? ├─ 0 : 127/148 └─ -1 : 130/150 ##### nfoldCV Classification Tree ##### Testing nfoldCV_tree Mean Accuracy: 0.8658658658658659 Mean Accuracy: 0.8528528528528528 Mean Accuracy: 0.8658658658658659 Mean Accuracy: 0.8658658658658659 Mean Accuracy: 0.8658658658658659 Mean Accuracy: 0.8658658658658659 Mean Accuracy: 0.8608608608608609 Mean Accuracy: 0.8608608608608609 Mean Accuracy: 0.8658658658658659 Mean Accuracy: 0.8658658658658659 Mean Accuracy: 0.8688688688688688 Mean Accuracy: 0.8688688688688688 ##### nfoldCV Classification Forest ##### Testing nfoldCV_forest Mean Accuracy: 0.908908908908909 Mean Accuracy: 0.8948948948948949 Mean Accuracy: 0.908908908908909 Mean Accuracy: 0.908908908908909 Mean Accuracy: 0.9059059059059059 Mean Accuracy: 0.9059059059059059 Mean Accuracy: 0.903903903903904 Mean Accuracy: 0.903903903903904 Mean Accuracy: 0.8978978978978978 Mean Accuracy: 0.8978978978978978 Mean Accuracy: 0.9029029029029029 Mean Accuracy: 0.9029029029029029 Fold 1 Classes: [-2, -1, 0, 1] Matrix: 4×4 Matrix{Int64}: 5 4 0 0 1 136 7 0 0 15 154 0 0 0 11 0 Accuracy: 0.8858858858858859 Kappa: 0.7871381230339631 Fold 2 Classes: [-2, -1, 0, 1] Matrix: 4×4 Matrix{Int64}: 3 2 0 0 1 146 11 0 0 13 152 2 0 0 2 1 Accuracy: 0.9069069069069069 Kappa: 0.8216081704598475 Fold 3 Classes: [-2, -1, 0, 1] Matrix: 4×4 Matrix{Int64}: 3 12 0 0 0 137 12 0 0 9 155 1 0 0 3 1 Accuracy: 0.8888888888888888 Kappa: 0.7920295726149482 Mean Accuracy: 0.8938938938938938 ##### nfoldCV Adaboosted Stumps ##### Testing nfoldCV_stumps Mean Accuracy: 0.8818818818818818 Mean Accuracy: 0.8828828828828829 Mean Accuracy: 0.8818818818818818 Mean Accuracy: 0.8818818818818818 Mean Accuracy: 0.9009009009009009 Mean Accuracy: 0.9009009009009009 Mean Accuracy: 0.8908908908908909 Mean Accuracy: 0.8908908908908909 Mean Accuracy: 0.8898898898898899 Mean Accuracy: 0.8898898898898899 Mean Accuracy: 0.883883883883884 Mean Accuracy: 0.883883883883884 ================================================== TEST: classification/low_precision.jl ##### nfoldCV Classification Tree ##### Fold 1 Classes: Int32[-2, -1, 0, 1] Matrix: 4×4 Matrix{Int64}: 23 0 0 0 2 136 1 0 0 7 144 1 0 0 1 18 Accuracy: 0.963963963963964 Kappa: 0.9411348771433623 Fold 2 Classes: Int32[-2, -1, 0, 1] Matrix: 4×4 Matrix{Int64}: 19 4 0 0 1 149 6 0 0 8 126 0 0 0 3 17 Accuracy: 0.933933933933934 Kappa: 0.8904654396483414 Fold 3 Classes: Int32[-2, -1, 0, 1] Matrix: 4×4 Matrix{Int64}: 17 0 0 0 0 134 3 0 0 0 151 0 0 0 0 28 Accuracy: 0.990990990990991 Kappa: 0.9853527652337104 Mean Accuracy: 0.9629629629629629 ##### nfoldCV Classification Forest ##### Fold 1 Classes: Int32[-2, -1, 0, 1] Matrix: 4×4 Matrix{Int64}: 12 11 0 0 0 134 5 0 0 8 143 1 0 0 3 16 Accuracy: 0.9159159159159159 Kappa: 0.8588790846210893 Fold 2 Classes: Int32[-2, -1, 0, 1] Matrix: 4×4 Matrix{Int64}: 14 9 0 0 0 145 11 0 0 9 120 5 0 0 1 19 Accuracy: 0.8948948948948949 Kappa: 0.8259694494632005 Fold 3 Classes: Int32[-2, -1, 0, 1] Matrix: 4×4 Matrix{Int64}: 14 3 0 0 0 133 4 0 0 3 143 5 0 0 1 27 Accuracy: 0.9519519519519519 Kappa: 0.9220642443391258 Mean Accuracy: 0.9209209209209209 ##### nfoldCV Adaboosted Stumps ##### Fold 1 Classes: Int32[-2, -1, 0, 1] Matrix: 4×4 Matrix{Int64}: 0 23 0 0 0 137 2 0 0 5 147 0 0 0 19 0 Accuracy: 0.8528528528528528 Kappa: 0.7385850235508987 Fold 2 Classes: Int32[-2, -1, 0, 1] Matrix: 4×4 Matrix{Int64}: 0 23 0 0 0 143 13 0 0 5 129 0 0 0 20 0 Accuracy: 0.8168168168168168 Kappa: 0.6750179985601152 Fold 3 Classes: Int32[-2, -1, 0, 1] Matrix: 4×4 Matrix{Int64}: 0 17 0 0 0 135 2 0 0 4 147 0 0 0 28 0 Accuracy: 0.8468468468468469 Kappa: 0.7295269947443861 Mean Accuracy: 0.8388388388388389 ================================================== TEST: classification/heterogeneous.jl ================================================== TEST: classification/digits.jl ================================================== TEST: classification/iris.jl Feature 4 < 0.8 ? ├─ Iris-setosa : 50/50 └─ Feature 4 < 1.75 ? ├─ Feature 3 < 4.95 ? ├─ Feature 4 < 1.65 ? ├─ Iris-versicolor : 47/47 └─ Iris-virginica : 1/1 └─ Feature 4 < 1.55 ? ├─ Iris-virginica : 3/3 └─ Feature 3 < 5.45 ? ├─ Iris-versicolor : 2/2 └─ Iris-virginica : 1/1 └─ Feature 3 < 4.85 ? ├─ Feature 1 < 5.95 ? ├─ Iris-versicolor : 1/1 └─ Iris-virginica : 2/2 └─ Iris-virginica : 43/43 ##### nfoldCV Classification Tree ##### Fold 1 Classes: ["Iris-setosa", "Iris-versicolor", "Iris-virginica"] Matrix: 3×3 Matrix{Int64}: 20 0 0 0 18 3 0 0 9 Accuracy: 0.94 Kappa: 0.9070631970260222 Fold 2 Classes: ["Iris-setosa", "Iris-versicolor", "Iris-virginica"] Matrix: 3×3 Matrix{Int64}: 15 0 0 0 15 1 0 1 18 Accuracy: 0.96 Kappa: 0.9396863691194209 Fold 3 Classes: ["Iris-setosa", "Iris-versicolor", "Iris-virginica"] Matrix: 3×3 Matrix{Int64}: 15 0 0 0 13 0 0 6 16 Accuracy: 0.88 Kappa: 0.8210023866348449 Mean Accuracy: 0.9266666666666666 ##### nfoldCV Classification Forest ##### Fold 1 Classes: ["Iris-setosa", "Iris-versicolor", "Iris-virginica"] Matrix: 3×3 Matrix{Int64}: 20 0 0 0 19 2 0 1 8 Accuracy: 0.94 Kappa: 0.9056603773584905 Fold 2 Classes: ["Iris-setosa", "Iris-versicolor", "Iris-virginica"] Matrix: 3×3 Matrix{Int64}: 15 0 0 0 15 1 0 3 16 Accuracy: 0.92 Kappa: 0.8798076923076925 Fold 3 Classes: ["Iris-setosa", "Iris-versicolor", "Iris-virginica"] Matrix: 3×3 Matrix{Int64}: 15 0 0 0 13 0 0 6 16 Accuracy: 0.88 Kappa: 0.8210023866348449 Mean Accuracy: 0.9133333333333332 ##### nfoldCV Classification Adaboosted Stumps ##### Fold 1 Classes: ["Iris-setosa", "Iris-versicolor", "Iris-virginica"] Matrix: 3×3 Matrix{Int64}: 20 0 0 0 19 2 0 0 9 Accuracy: 0.96 Kappa: 0.9375780274656679 Fold 2 Classes: ["Iris-setosa", "Iris-versicolor", "Iris-virginica"] Matrix: 3×3 Matrix{Int64}: 15 0 0 0 14 2 0 2 17 Accuracy: 0.92 Kappa: 0.879372738238842 Fold 3 Classes: ["Iris-setosa", "Iris-versicolor", "Iris-virginica"] Matrix: 3×3 Matrix{Int64}: 15 0 0 0 13 0 0 6 16 Accuracy: 0.88 Kappa: 0.8210023866348449 Mean Accuracy: 0.9199999999999999 ================================================== TEST: classification/adult.jl ##### 3 foldCV Classification Tree ##### Mean Accuracy: 0.8109892809975735 ##### 3 foldCV Classification Forest ##### Mean Accuracy: 0.8413341933106054 ##### nfoldCV Classification Adaboosted Stumps ##### Mean Accuracy: 0.8350686446143923 ================================================== TEST: classification/scikitlearn.jl ================================================== TEST: classification/adding_trees.jl ================================================== TEST: regression/random.jl ================================================== TEST: regression/low_precision.jl ##### nfoldCV Regression Tree ##### Fold 1 Mean Squared Error: 1.90132078391519 Correlation Coeff: 0.8974037382149184 Coeff of Determination: 0.8045191633321014 Fold 2 Mean Squared Error: 1.6017569471454187 Correlation Coeff: 0.9157999659106489 Coeff of Determination: 0.8384365213936864 Fold 3 Mean Squared Error: 1.5986344693657724 Correlation Coeff: 0.9123272177000765 Coeff of Determination: 0.8214814920817384 Mean Coeff of Determination: 0.821479058935842 ##### nfoldCV Regression Forest ##### Fold 1 Mean Squared Error: 1.2353634596621743 Correlation Coeff: 0.9467692443993198 Coeff of Determination: 0.8729883538187402 Fold 2 Mean Squared Error: 1.3297177364601998 Correlation Coeff: 0.9564527935419951 Coeff of Determination: 0.8658761409152053 Fold 3 Mean Squared Error: 1.1170134745442588 Correlation Coeff: 0.9507514465365862 Coeff of Determination: 0.8752638063163086 Mean Coeff of Determination: 0.8713761003500847 ================================================== TEST: regression/digits.jl ##### 3 foldCV Regression Tree ##### Mean Coeff of Determination: 0.6349826429860214 ##### 3 foldCV Regression Forest ##### Mean Coeff of Determination: 0.6324059967649163 ================================================== TEST: regression/scikitlearn.jl ================================================== TEST: miscellaneous/convert.jl ================================================== TEST: miscellaneous/abstract_trees_test.jl [ Info: Test base functionality [ Info: -- Tree with feature names and class labels firstFt < 0.7 ├─ a (2/3) └─ secondFt < 0.5 ├─ b (2/3) └─ c (2/3) [ Info: -- Tree with feature names firstFt < 0.7 ├─ Class: 1 (2/3) └─ secondFt < 0.5 ├─ Class: 2 (2/3) └─ Class: 3 (2/3) [ Info: -- Tree with class labels Feature: 1 < 0.7 ├─ a (2/3) └─ Feature: 2 < 0.5 ├─ b (2/3) └─ c (2/3) [ Info: -- Tree with ids only (nonsense parameters) Feature: 1 < 0.7 ├─ Class: 1 (2/3) └─ Feature: 2 < 0.5 ├─ Class: 2 (2/3) └─ Class: 3 (2/3) [ Info: -- Tree with ids only Feature: 1 < 0.7 ├─ Class: 1 (2/3) └─ Feature: 2 < 0.5 ├─ Class: 2 (2/3) └─ Class: 3 (2/3) [ Info: Test `children` with 'adult' decision tree [ Info: -- Preparing test data [ Info: -- Test `children` [ Info: Test misuse of `classlabel` information [ Info: Create test data - a decision tree based on the iris data set [ Info: Try to replace the exisitng class labels Feature: 4 < 0.8 ├─ ================================================== TEST: miscellaneous/feature_importance_test.jl feature_importance_test.jl: Test Failed at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/test/miscellaneous/feature_importance_test.jl:210 Expression: sum(f1[1:2]) < 0.1 Evaluated: 0.10201737083913823 < 0.1 Stacktrace: [1] top-level scope @ ~/.julia/packages/DecisionTree/0Dw1P/test/miscellaneous/feature_importance_test.jl:2 [2] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1929 [inlined] [3] macro expansion @ ~/.julia/packages/DecisionTree/0Dw1P/test/miscellaneous/feature_importance_test.jl:210 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:745 [inlined] feature_importance_test.jl: Test Failed at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/test/miscellaneous/feature_importance_test.jl:211 Expression: 0.35 < f1[3] - f1[4] < 0.45 Evaluated: 0.35 < 0.10830308228329055 < 0.45 Stacktrace: [1] top-level scope @ ~/.julia/packages/DecisionTree/0Dw1P/test/miscellaneous/feature_importance_test.jl:2 [2] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1929 [inlined] [3] macro expansion @ ~/.julia/packages/DecisionTree/0Dw1P/test/miscellaneous/feature_importance_test.jl:211 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:745 [inlined] feature_importance_test.jl: Test Failed at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/test/miscellaneous/feature_importance_test.jl:235 Expression: 0.85 < (split_importance(model, coeffs))[3] < 0.95 Evaluated: 0.85 < 1.0 < 0.95 Stacktrace: [1] top-level scope @ ~/.julia/packages/DecisionTree/0Dw1P/test/miscellaneous/feature_importance_test.jl:2 [2] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:1929 [inlined] [3] macro expansion @ ~/.julia/packages/DecisionTree/0Dw1P/test/miscellaneous/feature_importance_test.jl:235 [inlined] [4] macro expansion @ /opt/julia/share/julia/stdlib/v1.13/Test/src/Test.jl:745 [inlined] ================================================== TEST: miscellaneous/ensemble_methods.jl ================================================== Test Summary: | Pass Fail Total Time Test Suites | 9631 3 9634 5m51.5s Classification | 150 150 4m25.6s Regression | 43 43 44.3s Miscellaneous | 9438 3 9441 41.6s convert.jl | 9 9 1.0s convert to text | 0 0.5s abstract_trees_test.jl | 9378 9378 8.4s abstract_trees - test misuse | 1 1 1.1s feature_importance_test.jl | 38 3 41 24.5s methods for `Ensemble` type | 12 12 5.4s RNG of the outermost testset: Xoshiro(0x180b0a4e0958500b, 0x73fbdb0591af5a23, 0xd312b15c33602f0a, 0x9cbd598475c1c25b, 0xdc8984caf7939a23) ERROR: LoadError: Some tests did not pass: 9631 passed, 3 failed, 0 errored, 0 broken. in expression starting at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/test/runtests.jl:61 Testing failed after 358.95s ERROR: LoadError: Package DecisionTree errored during testing Stacktrace: [1] pkgerror(msg::String) @ Pkg.Types /opt/julia/share/julia/stdlib/v1.13/Pkg/src/Types.jl:68 [2] test(ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}; coverage::Bool, julia_args::Cmd, test_args::Cmd, test_fn::Nothing, force_latest_compatible_version::Bool, allow_earlier_backwards_compatible_versions::Bool, allow_reresolve::Bool) @ Pkg.Operations /opt/julia/share/julia/stdlib/v1.13/Pkg/src/Operations.jl:2672 [3] test @ /opt/julia/share/julia/stdlib/v1.13/Pkg/src/Operations.jl:2521 [inlined] [4] test(ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}; coverage::Bool, test_fn::Nothing, julia_args::Cmd, test_args::Cmd, force_latest_compatible_version::Bool, allow_earlier_backwards_compatible_versions::Bool, allow_reresolve::Bool, kwargs::@Kwargs{io::IOContext{IO}}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:538 [5] kwcall(::@NamedTuple{julia_args::Cmd, io::IOContext{IO}}, ::typeof(Pkg.API.test), ctx::Pkg.Types.Context, pkgs::Vector{PackageSpec}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:515 [6] test(pkgs::Vector{PackageSpec}; io::IOContext{IO}, kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:168 [7] kwcall(::@NamedTuple{julia_args::Cmd}, ::typeof(Pkg.API.test), pkgs::Vector{PackageSpec}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:157 [8] test(pkgs::Vector{String}; kwargs::@Kwargs{julia_args::Cmd}) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:156 [9] test @ /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:156 [inlined] [10] kwcall(::@NamedTuple{julia_args::Cmd}, ::typeof(Pkg.API.test), pkg::String) @ Pkg.API /opt/julia/share/julia/stdlib/v1.13/Pkg/src/API.jl:155 [11] top-level scope @ /PkgEval.jl/scripts/evaluate.jl:219 [12] include(mod::Module, _path::String) @ Base ./Base.jl:308 [13] exec_options(opts::Base.JLOptions) @ Base ./client.jl:330 [14] _start() @ Base ./client.jl:563 in expression starting at /PkgEval.jl/scripts/evaluate.jl:210 PkgEval failed after 404.84s: package has test failures