Package evaluation of EvoTrees on Julia 1.11.4 (a71dd056e0*) started at 2025-04-08T14:11:51.496


################################################################################
# Set-up
#

Installing PkgEval dependencies (TestEnv)...

Set-up completed after 8.64s


################################################################################
# Installation
#

Installing EvoTrees...
   Resolving package versions...
    Updating `~/.julia/environments/v1.11/Project.toml`
  [f6006082] + EvoTrees v0.17.2
    Updating `~/.julia/environments/v1.11/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 v0.25.118
  [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 v0.5.7
  [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 v1.11.0
  [e1d29d7a] + Missings v1.2.0
  [46757867] + NetworkLayout v0.4.10
  [bac558e1] + OrderedCollections v1.8.0
  [90014a1f] + PDMats v0.11.33
⌅ [aea7be01] + PrecompileTools v1.2.1
  [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 v2.5.0
  [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 v0.34.4
  [4c63d2b9] + StatsFuns v1.4.0
  [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 v1.6.0
  [7b1f6079] + FileWatching v1.11.0
  [9fa8497b] + Future v1.11.0
  [b77e0a4c] + InteractiveUtils v1.11.0
  [b27032c2] + LibCURL v0.6.4
  [76f85450] + LibGit2 v1.11.0
  [8f399da3] + Libdl v1.11.0
  [37e2e46d] + LinearAlgebra v1.11.0
  [56ddb016] + Logging v1.11.0
  [d6f4376e] + Markdown v1.11.0
  [ca575930] + NetworkOptions v1.2.0
  [44cfe95a] + Pkg v1.11.0
  [de0858da] + Printf v1.11.0
  [9a3f8284] + Random v1.11.0
  [ea8e919c] + SHA v0.7.0
  [9e88b42a] + Serialization v1.11.0
  [2f01184e] + SparseArrays 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 v1.1.1+0
  [deac9b47] + LibCURL_jll v8.6.0+0
  [e37daf67] + LibGit2_jll v1.7.2+0
  [29816b5a] + LibSSH2_jll v1.11.0+1
  [c8ffd9c3] + MbedTLS_jll v2.28.6+0
  [14a3606d] + MozillaCACerts_jll v2023.12.12
  [4536629a] + OpenBLAS_jll v0.3.27+1
  [05823500] + OpenLibm_jll v0.8.5+0
  [bea87d4a] + SuiteSparse_jll v7.7.0+0
  [83775a58] + Zlib_jll v1.2.13+1
  [8e850b90] + libblastrampoline_jll v5.11.0+0
  [8e850ede] + nghttp2_jll v1.59.0+0
  [3f19e933] + p7zip_jll v17.4.0+2
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m`

Installation completed after 4.18s


################################################################################
# Precompilation
#

Precompiling PkgEval dependencies...

Precompiling package dependencies...

Precompilation completed after 270.59s


################################################################################
# Testing
#

     Testing EvoTrees
      Status `/tmp/jl_LT06s0/Project.toml`
  [fbb218c0] BSON v0.3.9
  [052768ef] CUDA v5.7.2
  [324d7699] CategoricalArrays v0.10.8
  [a93c6f00] DataFrames v1.7.0
  [31c24e10] Distributions v0.25.118
  [f6006082] EvoTrees v0.17.2
  [a7f614a8] MLJBase v1.8.1
  [e80e1ace] MLJModelInterface v1.11.0
  [72560011] MLJTestInterface v0.2.8
  [46757867] NetworkLayout v0.4.10
  [3cdcf5f2] RecipesBase v1.3.4
  [10745b16] Statistics v1.11.1
  [2913bbd2] StatsBase v0.34.4
  [bd369af6] Tables v1.12.0
  [9a3f8284] Random v1.11.0
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_LT06s0/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 v5.7.2
  [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 v0.25.118
  [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 v1.3.2
  [096a3bc2] GPUToolbox v0.2.0
  [68eda718] GeoFormatTypes v0.4.4
  [cf35fbd7] GeoInterface v1.4.1
  [5c1252a2] GeometryBasics v0.5.7
  [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 v9.2.0
  [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 v1.11.0
  [72560011] MLJTestInterface v0.2.8
  [d8e11817] MLStyle v0.4.17
  [f1d291b0] MLUtils v0.4.8
  [1914dd2f] MacroTools v0.5.15
  [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 v0.11.33
  [d96e819e] Parameters v0.12.3
  [2dfb63ee] PooledArrays v1.4.3
⌅ [aea7be01] PrecompileTools v1.2.1
  [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 v2.5.0
  [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 v0.34.4
  [4c63d2b9] StatsFuns v1.4.0
  [892a3eda] StringManipulation v0.4.1
  [3783bdb8] TableTraits v1.0.1
  [bd369af6] Tables v1.12.0
  [a759f4b9] TimerOutputs v0.5.28
  [28d57a85] Transducers v0.4.84
  [3a884ed6] UnPack v1.0.2
  [013be700] UnsafeAtomics v0.3.0
  [4ee394cb] CUDA_Driver_jll v0.12.1+1
  [76a88914] CUDA_Runtime_jll v0.16.1+0
  [5ae413db] EarCut_jll v2.2.4+0
  [9c1d0b0a] JuliaNVTXCallbacks_jll v0.2.1+0
  [dad2f222] LLVMExtra_jll v0.0.35+0
  [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 v1.6.0
  [7b1f6079] FileWatching v1.11.0
  [9fa8497b] Future v1.11.0
  [b77e0a4c] InteractiveUtils v1.11.0
  [4af54fe1] LazyArtifacts v1.11.0
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.11.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [a63ad114] Mmap v1.11.0
  [ca575930] NetworkOptions v1.2.0
  [44cfe95a] Pkg v1.11.0
  [de0858da] Printf 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 v1.11.0
  [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 v1.1.1+0
  [deac9b47] LibCURL_jll v8.6.0+0
  [e37daf67] LibGit2_jll v1.7.2+0
  [29816b5a] LibSSH2_jll v1.11.0+1
  [c8ffd9c3] MbedTLS_jll v2.28.6+0
  [14a3606d] MozillaCACerts_jll v2023.12.12
  [4536629a] OpenBLAS_jll v0.3.27+1
  [05823500] OpenLibm_jll v0.8.5+0
  [bea87d4a] SuiteSparse_jll v7.7.0+0
  [83775a58] Zlib_jll v1.2.13+1
  [8e850b90] libblastrampoline_jll v5.11.0+0
  [8e850ede] nghttp2_jll v1.59.0+0
  [3f19e933] p7zip_jll v17.4.0+2
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading.
     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 MLJBase...
   1313.9 ms  ✓ BangBang → BangBangTablesExt
   2851.0 ms  ✓ MLCore
  13241.3 ms  ✓ NNlib
   8345.7 ms  ✓ ScientificTypes
   9369.3 ms  ✓ Transducers
   2307.8 ms  ✓ NNlib → NNlibSpecialFunctionsExt
   8542.2 ms  ✓ CategoricalDistributions
   2787.4 ms  ✓ Transducers → TransducersAdaptExt
  15715.6 ms  ✓ FLoops
  20306.1 ms  ✓ MLUtils
  18241.5 ms  ✓ StatisticalMeasuresBase
  17971.2 ms  ✓ MLJBase
  12 dependencies successfully precompiled in 124 seconds. 131 already precompiled.
Precompiling BangBangDataFramesExt...
   4437.6 ms  ✓ BangBang → BangBangDataFramesExt
  1 dependency successfully precompiled in 5 seconds. 45 already precompiled.
Precompiling TransducersDataFramesExt...
   4328.7 ms  ✓ Transducers → TransducersDataFramesExt
  1 dependency successfully precompiled in 5 seconds. 61 already precompiled.
Precompiling MLJTestInterface...
  13965.0 ms  ✓ MLJTestInterface
  1 dependency successfully precompiled in 16 seconds. 158 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  17m07.5s
     Testing EvoTrees tests passed 

Testing completed after 1031.11s

PkgEval succeeded after 1341.47s