Package evaluation of EvoTrees on Julia 1.13.0-DEV.582 (c0a1728d50*) started at 2025-05-14T13:59:57.252 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 7.92s ################################################################################ # Installation # Installing EvoTrees... Resolving package versions... Updating `~/.julia/environments/v1.13/Project.toml` [f6006082] + EvoTrees v0.17.2 Updating `~/.julia/environments/v1.13/Manifest.toml` [66dad0bd] + AliasTables v1.1.3 [fbb218c0] + BSON v0.3.9 [324d7699] + CategoricalArrays v0.10.8 [34da2185] + Compat v4.16.0 [9a962f9c] + DataAPI v1.16.0 [864edb3b] + DataStructures v0.18.22 [e2d170a0] + DataValueInterfaces v1.0.0 [31c24e10] + Distributions v0.25.120 [ffbed154] + DocStringExtensions v0.9.4 [f6006082] + EvoTrees v0.17.2 [411431e0] + Extents v0.1.5 [1a297f60] + FillArrays v1.13.0 [68eda718] + GeoFormatTypes v0.4.4 [cf35fbd7] + GeoInterface v1.4.1 [5c1252a2] + GeometryBasics v0.5.9 [34004b35] + HypergeometricFunctions v0.3.28 [92d709cd] + IrrationalConstants v0.2.4 [c8e1da08] + IterTools v1.10.0 [82899510] + IteratorInterfaceExtensions v1.0.0 [692b3bcd] + JLLWrappers v1.7.0 [2ab3a3ac] + LogExpFunctions v0.3.29 [e80e1ace] + MLJModelInterface v1.11.1 [e1d29d7a] + Missings v1.2.0 [46757867] + NetworkLayout v0.4.10 [bac558e1] + OrderedCollections v1.8.0 [90014a1f] + PDMats v0.11.35 [aea7be01] + PrecompileTools v1.3.2 [21216c6a] + Preferences v1.4.3 [43287f4e] + PtrArrays v1.3.0 [1fd47b50] + QuadGK v2.11.2 [3cdcf5f2] + RecipesBase v1.3.4 [189a3867] + Reexport v1.2.2 [ae029012] + Requires v1.3.1 [79098fc4] + Rmath v0.8.0 [30f210dd] + ScientificTypesBase v3.0.0 [a2af1166] + SortingAlgorithms v1.2.1 [276daf66] + SpecialFunctions v2.5.1 [90137ffa] + StaticArrays v1.9.13 [1e83bf80] + StaticArraysCore v1.4.3 [64bff920] + StatisticalTraits v3.4.0 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.7.0 [2913bbd2] + StatsBase v0.34.5 [4c63d2b9] + StatsFuns v1.5.0 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.0 [5ae413db] + EarCut_jll v2.2.4+0 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [f50d1b31] + Rmath_jll v0.5.1+0 [0dad84c5] + ArgTools v1.1.2 [56f22d72] + Artifacts v1.11.0 [2a0f44e3] + Base64 v1.11.0 [ade2ca70] + Dates v1.11.0 [f43a241f] + Downloads v1.7.0 [7b1f6079] + FileWatching v1.11.0 [9fa8497b] + Future v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.12.0 [b27032c2] + LibCURL v0.6.4 [76f85450] + LibGit2 v1.11.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.12.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [ca575930] + NetworkOptions v1.3.0 [44cfe95a] + Pkg v1.13.0 [de0858da] + Printf v1.11.0 [3fa0cd96] + REPL v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v0.7.0 [9e88b42a] + Serialization v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.12.0 [f489334b] + StyledStrings v1.11.0 [4607b0f0] + SuiteSparse [fa267f1f] + TOML v1.0.3 [a4e569a6] + Tar v1.10.0 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] + LibCURL_jll v8.12.1+1 [e37daf67] + LibGit2_jll v1.9.0+0 [29816b5a] + LibSSH2_jll v1.11.3+1 [14a3606d] + MozillaCACerts_jll v2025.2.25 [4536629a] + OpenBLAS_jll v0.3.29+0 [05823500] + OpenLibm_jll v0.8.5+0 [458c3c95] + OpenSSL_jll v3.5.0+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.1+2 [8e850b90] + libblastrampoline_jll v5.12.0+0 [8e850ede] + nghttp2_jll v1.65.0+0 [3f19e933] + p7zip_jll v17.5.0+2 Installation completed after 3.83s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 275.06s ################################################################################ # Testing # Testing EvoTrees Status `/tmp/jl_6T9N0a/Project.toml` [fbb218c0] BSON v0.3.9 [052768ef] CUDA v5.8.0 [324d7699] CategoricalArrays v0.10.8 [a93c6f00] DataFrames v1.7.0 [31c24e10] Distributions v0.25.120 [f6006082] EvoTrees v0.17.2 [a7f614a8] MLJBase v1.8.1 [e80e1ace] MLJModelInterface v1.11.1 [72560011] MLJTestInterface v0.2.8 [46757867] NetworkLayout v0.4.10 [3cdcf5f2] RecipesBase v1.3.4 [10745b16] Statistics v1.11.1 [2913bbd2] StatsBase v0.34.5 [bd369af6] Tables v1.12.0 [9a3f8284] Random v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_6T9N0a/Manifest.toml` [621f4979] AbstractFFTs v1.5.0 [7d9f7c33] Accessors v0.1.42 [79e6a3ab] Adapt v4.3.0 [66dad0bd] AliasTables v1.1.3 [dce04be8] ArgCheck v2.5.0 [a9b6321e] Atomix v1.1.1 [ab4f0b2a] BFloat16s v0.5.1 [fbb218c0] BSON v0.3.9 [198e06fe] BangBang v0.4.4 [9718e550] Baselet v0.1.1 [fa961155] CEnum v0.5.0 [052768ef] CUDA v5.8.0 [1af6417a] CUDA_Runtime_Discovery v0.3.5 [324d7699] CategoricalArrays v0.10.8 [af321ab8] CategoricalDistributions v0.1.15 [d360d2e6] ChainRulesCore v1.25.1 [3da002f7] ColorTypes v0.12.1 [5ae59095] Colors v0.13.0 [34da2185] Compat v4.16.0 [a33af91c] CompositionsBase v0.1.2 [ed09eef8] ComputationalResources v0.3.2 [187b0558] ConstructionBase v1.5.8 [6add18c4] ContextVariablesX v0.1.3 [a8cc5b0e] Crayons v4.1.1 [9a962f9c] DataAPI v1.16.0 [a93c6f00] DataFrames v1.7.0 [864edb3b] DataStructures v0.18.22 [e2d170a0] DataValueInterfaces v1.0.0 [244e2a9f] DefineSingletons v0.1.2 [8bb1440f] DelimitedFiles v1.9.1 [31c24e10] Distributions v0.25.120 [ffbed154] DocStringExtensions v0.9.4 [f6006082] EvoTrees v0.17.2 [e2ba6199] ExprTools v0.1.10 [411431e0] Extents v0.1.5 [cc61a311] FLoops v0.2.2 [b9860ae5] FLoopsBase v0.1.1 [1a297f60] FillArrays v1.13.0 [53c48c17] FixedPointNumbers v0.8.5 [0c68f7d7] GPUArrays v11.2.2 [46192b85] GPUArraysCore v0.2.0 [61eb1bfa] GPUCompiler v1.4.1 [096a3bc2] GPUToolbox v0.2.0 [68eda718] GeoFormatTypes v0.4.4 [cf35fbd7] GeoInterface v1.4.1 [5c1252a2] GeometryBasics v0.5.9 [076d061b] HashArrayMappedTries v0.2.0 [34004b35] HypergeometricFunctions v0.3.28 [22cec73e] InitialValues v0.3.1 [842dd82b] InlineStrings v1.4.3 [3587e190] InverseFunctions v0.1.17 [41ab1584] InvertedIndices v1.3.1 [92d709cd] IrrationalConstants v0.2.4 [c8e1da08] IterTools v1.10.0 [82899510] IteratorInterfaceExtensions v1.0.0 [692b3bcd] JLLWrappers v1.7.0 [b14d175d] JuliaVariables v0.2.4 [63c18a36] KernelAbstractions v0.9.34 [929cbde3] LLVM v9.3.1 [8b046642] LLVMLoopInfo v1.0.0 [b964fa9f] LaTeXStrings v1.4.0 [92ad9a40] LearnAPI v1.0.1 [2ab3a3ac] LogExpFunctions v0.3.29 [c2834f40] MLCore v1.0.0 [a7f614a8] MLJBase v1.8.1 [e80e1ace] MLJModelInterface v1.11.1 [72560011] MLJTestInterface v0.2.8 [d8e11817] MLStyle v0.4.17 [f1d291b0] MLUtils v0.4.8 [1914dd2f] MacroTools v0.5.16 [128add7d] MicroCollections v0.2.0 [e1d29d7a] Missings v1.2.0 [872c559c] NNlib v0.9.30 [5da4648a] NVTX v1.0.0 [71a1bf82] NameResolution v0.1.5 [46757867] NetworkLayout v0.4.10 [bac558e1] OrderedCollections v1.8.0 [90014a1f] PDMats v0.11.35 [d96e819e] Parameters v0.12.3 [2dfb63ee] PooledArrays v1.4.3 [aea7be01] PrecompileTools v1.3.2 [21216c6a] Preferences v1.4.3 [8162dcfd] PrettyPrint v0.2.0 [08abe8d2] PrettyTables v2.4.0 [92933f4c] ProgressMeter v1.10.4 [43287f4e] PtrArrays v1.3.0 [1fd47b50] QuadGK v2.11.2 [74087812] Random123 v1.7.0 [e6cf234a] RandomNumbers v1.6.0 [3cdcf5f2] RecipesBase v1.3.4 [189a3867] Reexport v1.2.2 [ae029012] Requires v1.3.1 [79098fc4] Rmath v0.8.0 [321657f4] ScientificTypes v3.1.0 [30f210dd] ScientificTypesBase v3.0.0 [7e506255] ScopedValues v1.3.0 [6c6a2e73] Scratch v1.2.1 [91c51154] SentinelArrays v1.4.8 [efcf1570] Setfield v1.1.2 [605ecd9f] ShowCases v0.1.0 [699a6c99] SimpleTraits v0.9.4 [a2af1166] SortingAlgorithms v1.2.1 [276daf66] SpecialFunctions v2.5.1 [171d559e] SplittablesBase v0.1.15 [90137ffa] StaticArrays v1.9.13 [1e83bf80] StaticArraysCore v1.4.3 [c062fc1d] StatisticalMeasuresBase v0.1.2 [64bff920] StatisticalTraits v3.4.0 [10745b16] Statistics v1.11.1 [82ae8749] StatsAPI v1.7.0 [2913bbd2] StatsBase v0.34.5 [4c63d2b9] StatsFuns v1.5.0 [892a3eda] StringManipulation v0.4.1 [3783bdb8] TableTraits v1.0.1 [bd369af6] Tables v1.12.0 [e689c965] Tracy v0.1.4 [28d57a85] Transducers v0.4.84 [3a884ed6] UnPack v1.0.2 [013be700] UnsafeAtomics v0.3.0 [4ee394cb] CUDA_Driver_jll v0.13.0+0 [76a88914] CUDA_Runtime_jll v0.17.0+0 [5ae413db] EarCut_jll v2.2.4+0 [9c1d0b0a] JuliaNVTXCallbacks_jll v0.2.1+0 [dad2f222] LLVMExtra_jll v0.0.35+0 [ad6e5548] LibTracyClient_jll v0.9.1+6 [e98f9f5b] NVTX_jll v3.1.1+0 [efe28fd5] OpenSpecFun_jll v0.5.6+0 [f50d1b31] Rmath_jll v0.5.1+0 [1e29f10c] demumble_jll v1.3.0+0 [0dad84c5] ArgTools v1.1.2 [56f22d72] Artifacts v1.11.0 [2a0f44e3] Base64 v1.11.0 [ade2ca70] Dates v1.11.0 [8ba89e20] Distributed v1.11.0 [f43a241f] Downloads v1.7.0 [7b1f6079] FileWatching v1.11.0 [9fa8497b] Future v1.11.0 [b77e0a4c] InteractiveUtils v1.11.0 [ac6e5ff7] JuliaSyntaxHighlighting v1.12.0 [4af54fe1] LazyArtifacts v1.11.0 [b27032c2] LibCURL v0.6.4 [76f85450] LibGit2 v1.11.0 [8f399da3] Libdl v1.11.0 [37e2e46d] LinearAlgebra v1.12.0 [56ddb016] Logging v1.11.0 [d6f4376e] Markdown v1.11.0 [a63ad114] Mmap v1.11.0 [ca575930] NetworkOptions v1.3.0 [44cfe95a] Pkg v1.13.0 [de0858da] Printf v1.11.0 [3fa0cd96] REPL v1.11.0 [9a3f8284] Random v1.11.0 [ea8e919c] SHA v0.7.0 [9e88b42a] Serialization v1.11.0 [6462fe0b] Sockets v1.11.0 [2f01184e] SparseArrays v1.12.0 [f489334b] StyledStrings v1.11.0 [4607b0f0] SuiteSparse [fa267f1f] TOML v1.0.3 [a4e569a6] Tar v1.10.0 [8dfed614] Test v1.11.0 [cf7118a7] UUIDs v1.11.0 [4ec0a83e] Unicode v1.11.0 [e66e0078] CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] LibCURL_jll v8.12.1+1 [e37daf67] LibGit2_jll v1.9.0+0 [29816b5a] LibSSH2_jll v1.11.3+1 [14a3606d] MozillaCACerts_jll v2025.2.25 [4536629a] OpenBLAS_jll v0.3.29+0 [05823500] OpenLibm_jll v0.8.5+0 [458c3c95] OpenSSL_jll v3.5.0+0 [bea87d4a] SuiteSparse_jll v7.10.1+0 [83775a58] Zlib_jll v1.3.1+2 [8e850b90] libblastrampoline_jll v5.12.0+0 [8e850ede] nghttp2_jll v1.65.0+0 [3f19e933] p7zip_jll v17.5.0+2 Testing Running tests... ┌ Info: initialization └ metric = 0.12850542f0 ┌ Info: iter 25 └ metric = 0.02185348f0 ┌ Info: iter 50 └ metric = 0.020308787f0 ┌ Info: iter 75 └ metric = 0.020313632f0 ┌ Info: iter 100 └ metric = 0.020534294f0 ┌ Info: initialization └ metric = 0.67035264f0 ┌ Info: iter 25 └ metric = 0.4821388f0 ┌ Info: iter 50 └ metric = 0.4353515f0 ┌ Info: iter 75 └ metric = 0.42019957f0 ┌ Info: iter 100 └ metric = 0.4141053f0 ┌ Info: initialization └ metric = 1.470955f0 ┌ Info: iter 25 └ metric = 0.3449375f0 ┌ Info: iter 50 └ metric = 0.30455413f0 ┌ Info: iter 75 └ metric = 0.29813784f0 ┌ Info: iter 100 └ metric = 0.3031827f0 ┌ Info: initialization └ metric = 0.547109f0 ┌ Info: iter 25 └ metric = 0.15687165f0 ┌ Info: iter 50 └ metric = 0.113459595f0 ┌ Info: iter 75 └ metric = 0.103374764f0 ┌ Info: iter 100 └ metric = 0.100005604f0 ┌ Info: initialization └ metric = 0.32020843f0 ┌ Info: iter 25 └ metric = 0.15535697f0 ┌ Info: iter 50 └ metric = 0.11413632f0 ┌ Info: iter 75 └ metric = 0.101256855f0 ┌ Info: iter 100 └ metric = 0.09931885f0 ┌ Info: initialization └ metric = 0.16010422f0 ┌ Info: iter 25 └ metric = 0.06761947f0 ┌ Info: iter 50 └ metric = 0.05156571f0 ┌ Info: iter 75 └ metric = 0.049420856f0 ┌ Info: iter 100 └ metric = 0.04868334f0 ┌ Info: initialization └ metric = 0.29576486f0 ┌ Info: iter 25 └ metric = 0.0998211f0 ┌ Info: iter 50 └ metric = 0.07062817f0 ┌ Info: iter 75 └ metric = 0.060815603f0 ┌ Info: iter 100 └ metric = 0.05664133f0 ┌ Info: initialization └ metric = 0.52540255f0 ┌ Info: iter 25 └ metric = 1.6643243f0 ┌ Info: iter 50 └ metric = 1.7553916f0 ┌ Info: iter 75 └ metric = 1.6366466f0 ┌ Info: iter 100 └ metric = 1.5275011f0 ┌ Info: initialization └ metric = -1.795783f0 ┌ Info: iter 25 └ metric = -0.11804731f0 ┌ Info: iter 50 └ metric = -0.21671551f0 ┌ Info: iter 75 └ metric = -0.3314146f0 ┌ Info: iter 100 └ metric = -0.33276245f0 ┌ Info: initialization └ metric = 0.52540255f0 ┌ Info: iter 25 └ metric = 1.6643243f0 ┌ Info: iter 50 └ metric = 1.7553916f0 ┌ Info: iter 75 └ metric = 1.6366466f0 ┌ Info: iter 100 └ metric = 1.5275011f0 ┌ Info: initialization └ metric = 0.12850542f0 ┌ Info: iter 25 └ metric = 0.04232597f0 ┌ Info: iter 50 └ metric = 0.029923327f0 ┌ Info: iter 75 └ metric = 0.025185471f0 ┌ Info: iter 100 └ metric = 0.022735545f0 ┌ Info: iter 125 └ metric = 0.021428667f0 ┌ Info: iter 150 └ metric = 0.0206716f0 ┌ Info: iter 175 └ metric = 0.020286473f0 ┌ Info: iter 200 └ metric = 0.020073429f0 ┌ Info: initialization └ metric = 0.67035264f0 ┌ Info: iter 25 └ metric = 0.48615295f0 ┌ Info: iter 50 └ metric = 0.44964468f0 ┌ Info: iter 75 └ metric = 0.43358475f0 ┌ Info: iter 100 └ metric = 0.42384133f0 ┌ Info: iter 125 └ metric = 0.4180519f0 ┌ Info: iter 150 └ metric = 0.4138667f0 ┌ Info: iter 175 └ metric = 0.41095614f0 ┌ Info: iter 200 └ metric = 0.4088857f0 ┌ Info: initialization └ metric = 0.16010422f0 ┌ Info: iter 25 └ metric = 0.082254715f0 ┌ Info: iter 50 └ metric = 0.06437093f0 ┌ Info: iter 75 └ metric = 0.058238436f0 ┌ Info: iter 100 └ metric = 0.053899385f0 ┌ Info: iter 125 └ metric = 0.05104642f0 ┌ Info: iter 150 └ metric = 0.049477838f0 ┌ Info: iter 175 └ metric = 0.04871792f0 ┌ Info: iter 200 └ metric = 0.047906503f0 ┌ Info: initialization └ metric = 0.32020843f0 ┌ Info: iter 25 └ metric = 0.18655248f0 ┌ Info: iter 50 └ metric = 0.1481525f0 ┌ Info: iter 75 └ metric = 0.13184947f0 ┌ Info: iter 100 └ metric = 0.12151933f0 ┌ Info: iter 125 └ metric = 0.11525992f0 ┌ Info: iter 150 └ metric = 0.11076274f0 ┌ Info: iter 175 └ metric = 0.107419536f0 ┌ Info: iter 200 └ metric = 0.10508649f0 ┌ Info: initialization └ metric = 1.470955f0 ┌ Info: iter 25 └ metric = 0.49673897f0 ┌ Info: iter 50 └ metric = 0.44725803f0 ┌ Info: iter 75 └ metric = 0.42674634f0 ┌ Info: iter 100 └ metric = 0.41090682f0 ┌ Info: iter 125 └ metric = 0.39991233f0 ┌ Info: iter 150 └ metric = 0.3913018f0 ┌ Info: iter 175 └ metric = 0.3847888f0 ┌ Info: iter 200 └ metric = 0.38012657f0 ┌ Info: initialization └ metric = 0.547109f0 ┌ Info: iter 25 └ metric = 0.2191384f0 ┌ Info: iter 50 └ metric = 0.13720419f0 ┌ Info: iter 75 └ metric = 0.11385028f0 ┌ Info: iter 100 └ metric = 0.10443449f0 ┌ Info: iter 125 └ metric = 0.0995198f0 ┌ Info: iter 150 └ metric = 0.0970285f0 ┌ Info: iter 175 └ metric = 0.095517285f0 ┌ Info: iter 200 └ metric = 0.09495845f0 ┌ Info: initialization └ metric = 0.29576486f0 ┌ Info: iter 25 └ metric = 0.07575523f0 ┌ Info: iter 50 └ metric = 0.05538964f0 ┌ Info: iter 75 └ metric = 0.049304195f0 ┌ Info: iter 100 └ metric = 0.047351643f0 ┌ Info: iter 125 └ metric = 0.046716917f0 ┌ Info: iter 150 └ metric = 0.046530694f0 ┌ Info: iter 175 └ metric = 0.04654186f0 ┌ Info: iter 200 └ metric = 0.04664114f0 ┌ Info: initialization └ metric = 0.52540255f0 ┌ Info: iter 25 └ metric = 1.2444885f0 ┌ Info: iter 50 └ metric = 1.5074849f0 ┌ Info: iter 75 └ metric = 1.678007f0 ┌ Info: iter 100 └ metric = 1.7726103f0 ┌ Info: iter 125 └ metric = 1.8351439f0 ┌ Info: iter 150 └ metric = 1.8794245f0 ┌ Info: iter 175 └ metric = 1.9026347f0 ┌ Info: iter 200 └ metric = 1.9192891f0 ┌ Info: initialization └ metric = -1.795783f0 ┌ Info: iter 25 └ metric = -0.5233327f0 ┌ Info: iter 50 └ metric = -0.31267753f0 ┌ Info: iter 75 └ metric = -0.148208f0 ┌ Info: iter 100 └ metric = -0.0816431f0 ┌ Info: iter 125 └ metric = -0.043182086f0 ┌ Info: iter 150 └ metric = -0.036856543f0 ┌ Info: iter 175 └ metric = -0.0331363f0 ┌ Info: iter 200 └ metric = -0.041607056f0 ┌ Info: initialization └ metric = 0.6875354f0 ┌ Info: iter 50 └ metric = 0.29864076f0 ┌ Info: iter 100 └ metric = 0.27442652f0 ┌ Info: initialization └ metric = 0.1269269f0 ┌ Info: iter 25 └ metric = 0.03544954f0 ┌ Info: iter 50 └ metric = 0.022091053f0 ┌ Info: iter 75 └ metric = 0.01983946f0 ┌ Info: iter 100 └ metric = 0.019345528f0 ┌ Info: initialization └ metric = 0.1269269f0 ┌ Info: iter 25 └ metric = 0.03533316f0 ┌ Info: iter 50 └ metric = 0.021854104f0 ┌ Info: iter 75 └ metric = 0.019633152f0 ┌ Info: iter 100 └ metric = 0.01929916f0 ┌ Info: initialization └ metric = 0.020358963f0 ┌ Info: iter 25 └ metric = 0.004361601f0 ┌ Info: iter 50 └ metric = 0.0013782553f0 ┌ Info: iter 75 └ metric = 0.00082236936f0 ┌ Info: iter 100 └ metric = 0.00071697246f0 ┌ Info: iter 125 └ metric = 0.0006971923f0 ┌ Info: iter 150 └ metric = 0.00069307245f0 ┌ Info: iter 175 └ metric = 0.00069179665f0 ┌ Info: iter 200 └ metric = 0.0006918938f0 ┌ Info: initialization └ metric = 0.020358963f0 ┌ Info: iter 25 └ metric = 0.0024131632f0 ┌ Info: iter 50 └ metric = 0.002412793f0 ┌ Info: iter 75 └ metric = 0.002414344f0 ┌ Info: iter 100 └ metric = 0.0024144694f0 ┌ Info: iter 125 └ metric = 0.0024142447f0 ┌ Info: iter 150 └ metric = 0.0024133387f0 ┌ Info: iter 175 └ metric = 0.002413443f0 ┌ Info: iter 200 └ metric = 0.0024133674f0 ┌ Info: initialization └ metric = 0.47385955f0 ┌ Info: iter 25 └ metric = 0.3655167f0 ┌ Info: iter 50 └ metric = 0.33879754f0 ┌ Info: iter 75 └ metric = 0.3307189f0 ┌ Info: iter 100 └ metric = 0.32773253f0 ┌ Info: iter 125 └ metric = 0.3264104f0 ┌ Info: iter 150 └ metric = 0.32573125f0 ┌ Info: iter 175 └ metric = 0.32533985f0 ┌ Info: iter 200 └ metric = 0.32509857f0 ┌ Info: initialization └ metric = 0.47385955f0 ┌ Info: iter 25 └ metric = 0.37179053f0 ┌ Info: iter 50 └ metric = 0.34909615f0 ┌ Info: iter 75 └ metric = 0.34352642f0 ┌ Info: iter 100 └ metric = 0.3420196f0 ┌ Info: iter 125 └ metric = 0.34157166f0 ┌ Info: iter 150 └ metric = 0.34141645f0 ┌ Info: iter 175 └ metric = 0.34136033f0 ┌ Info: iter 200 └ metric = 0.34133488f0 [ Info: The following kwargs are not supported and will be ignored: [:metric]. ┌ Info: initialization └ metric = 1.4467678f0 ┌ Info: iter 25 └ metric = 2.3832273f0 ┌ Info: iter 50 └ metric = 2.9961247f0 ┌ Info: iter 75 └ metric = 3.4032483f0 ┌ Info: iter 100 └ metric = 3.6399574f0 ┌ Info: iter 125 └ metric = 3.7699337f0 ┌ Info: iter 150 └ metric = 3.842246f0 ┌ Info: iter 175 └ metric = 3.8804824f0 ┌ Info: iter 200 └ metric = 3.8914828f0 ┌ Info: initialization └ metric = 1.4467678f0 ┌ Info: iter 25 └ metric = 2.695954f0 ┌ Info: iter 50 └ metric = 2.6968746f0 ┌ Info: iter 75 └ metric = 2.696397f0 ┌ Info: iter 100 └ metric = 2.696487f0 ┌ Info: iter 125 └ metric = 2.6961653f0 ┌ Info: iter 150 └ metric = 2.696897f0 ┌ Info: iter 175 └ metric = 2.696582f0 ┌ Info: iter 200 └ metric = 2.6968887f0 ┌ Info: initialization └ metric = 0.0067645954f0 Precompiling packages... 12915.5 ms ✓ NNlib 1404.3 ms ✓ StatsFuns → StatsFunsInverseFunctionsExt 8321.0 ms ✓ ScientificTypes 3121.7 ms ✓ NNlib → NNlibSpecialFunctionsExt 22697.5 ms ✓ MLUtils 8105.9 ms ✓ CategoricalDistributions 21160.0 ms ✓ StatisticalMeasuresBase 17903.3 ms ✓ MLJBase 8 dependencies successfully precompiled in 97 seconds. 138 already precompiled. Precompiling packages... 12954.9 ms ✓ BangBang → BangBangDataFramesExt 1 dependency successfully precompiled in 13 seconds. 47 already precompiled. Precompiling packages... 7992.2 ms ✓ Transducers → TransducersDataFramesExt 1 dependency successfully precompiled in 8 seconds. 63 already precompiled. Precompiling packages... 16382.4 ms ✓ MLJTestInterface 1 dependency successfully precompiled in 17 seconds. 162 already precompiled. ┌ Info: Training machine(EvoTreeRegressor │ - loss: logloss │ - metric: logloss │ - nrounds: 10 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.05 │ - max_depth: 5 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: MersenneTwister(123) │ - device: cpu └ , …). ┌ Info: Updating machine(EvoTreeRegressor │ - loss: logloss │ - metric: logloss │ - nrounds: 20 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.05 │ - max_depth: 5 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: MersenneTwister(123, (0, 2004, 1002, 908)) │ - device: cpu └ , …). ┌ Info: Training machine(EvoTreeClassifier │ - loss: mlogloss │ - metric: mlogloss │ - nrounds: 10 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.05 │ - max_depth: 4 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - tree_type: binary │ - rng: MersenneTwister(123) │ - device: cpu └ , …). ┌ Info: Updating machine(EvoTreeClassifier │ - loss: mlogloss │ - metric: mlogloss │ - nrounds: 60 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.05 │ - max_depth: 4 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - tree_type: binary │ - rng: MersenneTwister(123, (0, 1002, 0, 510)) │ - device: cpu └ , …). [ Info: The following kwargs are not supported and will be ignored: [:loss, :metric]. ┌ Info: Training machine(EvoTreeCount │ - loss: poisson │ - metric: poisson │ - nrounds: 10 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 0.5 │ - colsample: 0.5 │ - nbins: 32 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: MersenneTwister(123) │ - device: cpu └ , …). ┌ Info: Updating machine(EvoTreeCount │ - loss: poisson │ - metric: poisson │ - nrounds: 20 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 0.5 │ - colsample: 0.5 │ - nbins: 32 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: MersenneTwister(123, (0, 3006, 2004, 106)) │ - device: cpu └ , …). ┌ Info: Training machine(EvoTreeGaussian │ - loss: gaussian_mle │ - metric: gaussian_mle │ - nrounds: 10 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 0.5 │ - colsample: 0.5 │ - nbins: 32 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: MersenneTwister(123) │ - device: cpu └ , …). ┌ Info: Updating machine(EvoTreeGaussian │ - loss: gaussian_mle │ - metric: gaussian_mle │ - nrounds: 20 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 0.5 │ - colsample: 0.5 │ - nbins: 32 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: MersenneTwister(123, (0, 3006, 2004, 106)) │ - device: cpu └ , …). ┌ Info: Training machine(EvoTreeMLE │ - loss: logistic_mle │ - metric: logistic_mle │ - nrounds: 10 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 1.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 32.0 │ - rowsample: 0.5 │ - colsample: 0.5 │ - nbins: 32 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: MersenneTwister(123) │ - device: cpu └ , …). ┌ Info: Updating machine(EvoTreeMLE │ - loss: logistic_mle │ - metric: logistic_mle │ - nrounds: 20 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 1.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 32.0 │ - rowsample: 0.5 │ - colsample: 0.5 │ - nbins: 32 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: MersenneTwister(123, (0, 3006, 2004, 106)) │ - device: cpu └ , …). ┌ Info: Training machine(EvoTreeClassifier │ - loss: mlogloss │ - metric: mlogloss │ - nrounds: 100 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - tree_type: binary │ - rng: MersenneTwister(123) │ - device: cpu └ , …). ┌ Info: Training machine(EvoTreeRegressor │ - loss: mse │ - metric: mse │ - nrounds: 100 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: MersenneTwister(123) │ - device: cpu └ , …). ┌ Info: Training machine(EvoTreeRegressor │ - loss: logloss │ - metric: logloss │ - nrounds: 10 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 1.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 32.0 │ - rowsample: 0.5 │ - colsample: 0.5 │ - nbins: 32 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: MersenneTwister(123) │ - device: cpu └ , …). ┌ Info: Updating machine(EvoTreeRegressor │ - loss: logloss │ - metric: logloss │ - nrounds: 20 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 1.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 32.0 │ - rowsample: 0.5 │ - colsample: 0.5 │ - nbins: 32 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: MersenneTwister(123, (0, 3006, 2004, 106)) │ - device: cpu └ , …). ┌ Info: Training machine(EvoTreeRegressor │ - loss: mse │ - metric: mse │ - nrounds: 100 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: MersenneTwister(123) │ - device: cpu └ , …). ┌ Info: Not retraining machine(EvoTreeRegressor │ - loss: mse │ - metric: mse │ - nrounds: 100 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: MersenneTwister(123, (0, 18036, 17034, 866)) │ - device: cpu └ , …). Use `force=true` to force. ┌ Info: Training machine(EvoTreeRegressor │ - loss: mse │ - metric: mse │ - nrounds: 100 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: MersenneTwister(123) │ - device: cpu └ , …). ┌ Info: Not retraining machine(EvoTreeRegressor │ - loss: mse │ - metric: mse │ - nrounds: 100 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: MersenneTwister(123, (0, 18036, 17034, 866)) │ - device: cpu └ , …). Use `force=true` to force. ┌ Info: Training machine(EvoTreeClassifier │ - loss: mlogloss │ - metric: mlogloss │ - nrounds: 100 │ - early_stopping_rounds: 9223372036854775807 │ - L2: 1.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - tree_type: binary │ - rng: MersenneTwister(123) │ - device: cpu └ , …). Test Summary: | Pass Total Time EvoTrees | 87 87 14m44.6s Testing EvoTrees tests passed Testing completed after 906.0s PkgEval succeeded after 1214.38s