Package evaluation of EvoTrees on Julia 1.13.0-DEV.791 (d5209bd37d*) started at 2025-07-04T14:29:15.722


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

Installing PkgEval dependencies (TestEnv)...

Set-up completed after 8.49s


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

Installing EvoTrees...
   Resolving package versions...
    Updating `~/.julia/environments/v1.13/Project.toml`
  [f6006082] + EvoTrees v0.17.3
    Updating `~/.julia/environments/v1.13/Manifest.toml`
  [66dad0bd] + AliasTables v1.1.3
  [fbb218c0] + BSON v0.3.9
  [324d7699] + CategoricalArrays v0.10.8
  [34da2185] + Compat v4.17.0
  [9a962f9c] + DataAPI v1.16.0
  [864edb3b] + DataStructures v0.18.22
  [e2d170a0] + DataValueInterfaces v1.0.0
  [31c24e10] + Distributions v0.25.120
  [ffbed154] + DocStringExtensions v0.9.5
  [f6006082] + EvoTrees v0.17.3
  [411431e0] + Extents v0.1.6
  [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 v1.8.1
  [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 v1.7.1
  [2913bbd2] + StatsBase v0.34.5
  [4c63d2b9] + StatsFuns v1.5.0
  [3783bdb8] + TableTraits v1.0.1
  [bd369af6] + Tables v1.12.1
  [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 v8.14.1+1
  [e37daf67] + LibGit2_jll v1.9.1+0
  [29816b5a] + LibSSH2_jll v1.11.3+1
  [14a3606d] + MozillaCACerts_jll v2025.5.20
  [4536629a] + OpenBLAS_jll v0.3.29+0
  [05823500] + OpenLibm_jll v0.8.5+0
  [458c3c95] + OpenSSL_jll v3.5.0+0
  [efcefdf7] + PCRE2_jll v10.45.0+0
  [bea87d4a] + SuiteSparse_jll v7.10.1+0
  [83775a58] + Zlib_jll v1.3.1+2
  [8e850b90] + libblastrampoline_jll v5.13.1+0
  [8e850ede] + nghttp2_jll v1.65.0+0
  [3f19e933] + p7zip_jll v17.5.0+2

Installation completed after 4.08s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...

Precompilation completed after 405.8s


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

     Testing EvoTrees
      Status `/tmp/jl_MyptC4/Project.toml`
  [fbb218c0] BSON v0.3.9
  [052768ef] CUDA v5.8.2
  [324d7699] CategoricalArrays v0.10.8
  [a93c6f00] DataFrames v1.7.0
  [31c24e10] Distributions v0.25.120
  [f6006082] EvoTrees v0.17.3
  [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 v1.12.1
  [9a3f8284] Random v1.11.0
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_MyptC4/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 v5.8.2
  [1af6417a] CUDA_Runtime_Discovery v0.3.5
  [324d7699] CategoricalArrays v0.10.8
  [af321ab8] CategoricalDistributions v0.1.15
  [d360d2e6] ChainRulesCore v1.25.2
  [3da002f7] ColorTypes v0.12.1
  [5ae59095] Colors v0.13.1
  [34da2185] Compat v4.17.0
  [a33af91c] CompositionsBase v0.1.2
  [ed09eef8] ComputationalResources v0.3.2
  [187b0558] ConstructionBase v1.6.0
  [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 v0.9.5
  [f6006082] EvoTrees v0.17.3
  [e2ba6199] ExprTools v0.1.10
  [411431e0] Extents v0.1.6
  [cc61a311] FLoops v0.2.2
  [b9860ae5] FLoopsBase v0.1.1
  [1a297f60] FillArrays v1.13.0
  [53c48c17] FixedPointNumbers v0.8.5
  [0c68f7d7] GPUArrays v11.2.3
  [46192b85] GPUArraysCore v0.2.0
  [61eb1bfa] GPUCompiler v1.6.1
  [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 v1.4.4
  [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 v0.9.36
  [929cbde3] LLVM v9.4.2
  [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 v1.8.1
  [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 v1.7.1
  [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 v1.3.0
  [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 v1.7.1
  [2913bbd2] StatsBase v0.34.5
  [4c63d2b9] StatsFuns v1.5.0
  [892a3eda] StringManipulation v0.4.1
  [3783bdb8] TableTraits v1.0.1
  [bd369af6] Tables v1.12.1
  [e689c965] Tracy v0.1.5
  [28d57a85] Transducers v0.4.84
  [3a884ed6] UnPack v1.0.2
  [013be700] UnsafeAtomics v0.3.0
⌅ [4ee394cb] CUDA_Driver_jll v0.13.1+0
⌅ [76a88914] CUDA_Runtime_jll v0.17.1+0
  [5ae413db] EarCut_jll v2.2.4+0
  [9c1d0b0a] JuliaNVTXCallbacks_jll v0.2.1+0
  [dad2f222] LLVMExtra_jll v0.0.37+2
  [ad6e5548] LibTracyClient_jll v0.9.1+6
  [e98f9f5b] NVTX_jll v3.2.1+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 v8.14.1+1
  [e37daf67] LibGit2_jll v1.9.1+0
  [29816b5a] LibSSH2_jll v1.11.3+1
  [14a3606d] MozillaCACerts_jll v2025.5.20
  [4536629a] OpenBLAS_jll v0.3.29+0
  [05823500] OpenLibm_jll v0.8.5+0
  [458c3c95] OpenSSL_jll v3.5.0+0
  [efcefdf7] PCRE2_jll v10.45.0+0
  [bea87d4a] SuiteSparse_jll v7.10.1+0
  [83775a58] Zlib_jll v1.3.1+2
  [8e850b90] libblastrampoline_jll v5.13.1+0
  [8e850ede] nghttp2_jll v1.65.0+0
  [3f19e933] p7zip_jll v17.5.0+2
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading.
     Testing Running tests...
Precompiling packages...
   4362.0 ms  ✓ Distributions → DistributionsTestExt
  1 dependency successfully precompiled in 5 seconds. 49 already precompiled.
┌ Info: initialization
└   metric = 0.12850541855989803
┌ Info: iter 25
└   metric = 0.0218534840818225
┌ Info: iter 50
└   metric = 0.020308791952156183
┌ Info: iter 75
└   metric = 0.020313633117741006
┌ Info: iter 100
└   metric = 0.02053429553996752
┌ Info: initialization
└   metric = 0.6720977827906609
┌ Info: iter 25
└   metric = 0.4854209664463997
┌ Info: iter 50
└   metric = 0.4371707334369421
┌ Info: iter 75
└   metric = 0.42108118496835234
┌ Info: iter 100
└   metric = 0.41446558825671675
┌ Info: initialization
└   metric = 1.4709549355506897
┌ Info: iter 25
└   metric = 0.34493750214576724
┌ Info: iter 50
└   metric = 0.30455422043800356
┌ Info: iter 75
└   metric = 0.2981378662586212
┌ Info: iter 100
└   metric = 0.30318266987800596
┌ Info: initialization
└   metric = 0.5471089428663254
┌ Info: iter 25
└   metric = 0.1568716686964035
┌ Info: iter 50
└   metric = 0.11345964685082435
┌ Info: iter 75
└   metric = 0.10337476193904876
┌ Info: iter 100
└   metric = 0.10000559814274311
┌ Info: initialization
└   metric = 0.32020851522684096
┌ Info: iter 25
└   metric = 0.12922271866351365
┌ Info: iter 50
└   metric = 0.10199518817476928
┌ Info: iter 75
└   metric = 0.09919940970372408
┌ Info: iter 100
└   metric = 0.0991425906540826
┌ Info: initialization
└   metric = 0.16010425761342048
┌ Info: iter 25
└   metric = 0.060825394783169034
┌ Info: iter 50
└   metric = 0.049247815741691736
┌ Info: iter 75
└   metric = 0.04860964736551978
┌ Info: iter 100
└   metric = 0.04866470103792381
┌ Info: initialization
└   metric = 0.2957647952437401
┌ Info: iter 25
└   metric = 0.09982108637690544
┌ Info: iter 50
└   metric = 0.07062815807759762
┌ Info: iter 75
└   metric = 0.0608156019821763
┌ Info: iter 100
└   metric = 0.05664134617894888
┌ Info: initialization
└   metric = 0.5254025399684906
┌ Info: iter 25
└   metric = 1.6643243443965912
┌ Info: iter 50
└   metric = 1.7553918981552123
┌ Info: iter 75
└   metric = 1.6366464787721633
┌ Info: iter 100
└   metric = 1.527500919699669
┌ Info: initialization
└   metric = -1.7957830564654431
┌ Info: iter 25
└   metric = -0.11804731893353164
┌ Info: iter 50
└   metric = -0.2167155128903687
┌ Info: iter 75
└   metric = -0.3314145844290033
┌ Info: iter 100
└   metric = -0.33276243005879225
┌ Info: initialization
└   metric = 0.5254025399684906
┌ Info: iter 25
└   metric = 1.6643243443965912
┌ Info: iter 50
└   metric = 1.7553918981552123
┌ Info: iter 75
└   metric = 1.6366464787721633
┌ Info: iter 100
└   metric = 1.527500919699669
┌ Info: initialization
└   metric = 0.12850541855989803
┌ Info: iter 25
└   metric = 0.0423259663949284
┌ Info: iter 50
└   metric = 0.029923325241811655
┌ Info: iter 75
└   metric = 0.025185474146319962
┌ Info: iter 100
└   metric = 0.02273554716364629
┌ Info: iter 125
└   metric = 0.021428670910092932
┌ Info: iter 150
└   metric = 0.020671600587487547
┌ Info: iter 175
└   metric = 0.020286477897562917
┌ Info: iter 200
└   metric = 0.02007343324829222
┌ Info: initialization
└   metric = 0.6720977827906609
┌ Info: iter 25
└   metric = 0.48906796604394914
┌ Info: iter 50
└   metric = 0.45056863233447075
┌ Info: iter 75
└   metric = 0.4339840408042073
┌ Info: iter 100
└   metric = 0.42426158741116526
┌ Info: iter 125
└   metric = 0.41806680407375096
┌ Info: iter 150
└   metric = 0.41389062194153664
┌ Info: iter 175
└   metric = 0.4110515335574746
┌ Info: iter 200
└   metric = 0.4090116586722434
┌ Info: initialization
└   metric = 0.16010425761342048
┌ Info: iter 25
└   metric = 0.08159953819587827
┌ Info: iter 50
└   metric = 0.06353082546032965
┌ Info: iter 75
└   metric = 0.05730581597425043
┌ Info: iter 100
└   metric = 0.05306666763499379
┌ Info: iter 125
└   metric = 0.050234638033434746
┌ Info: iter 150
└   metric = 0.04865887098945677
┌ Info: iter 175
└   metric = 0.0479407334595453
┌ Info: iter 200
└   metric = 0.047474883199320174
┌ Info: initialization
└   metric = 0.32020851522684096
┌ Info: iter 25
└   metric = 0.1865524584800005
┌ Info: iter 50
└   metric = 0.14815250769257546
┌ Info: iter 75
└   metric = 0.13184949912130833
┌ Info: iter 100
└   metric = 0.12151799038052559
┌ Info: iter 125
└   metric = 0.11525779008865357
┌ Info: iter 150
└   metric = 0.1107572434656322
┌ Info: iter 175
└   metric = 0.10741648390889168
┌ Info: iter 200
└   metric = 0.1050634808279574
┌ Info: initialization
└   metric = 1.4709549355506897
┌ Info: iter 25
└   metric = 0.49673894643783567
┌ Info: iter 50
└   metric = 0.4472580850124359
┌ Info: iter 75
└   metric = 0.4267463994026184
┌ Info: iter 100
└   metric = 0.4109067535400391
┌ Info: iter 125
└   metric = 0.3999123275279999
┌ Info: iter 150
└   metric = 0.3913017475605011
┌ Info: iter 175
└   metric = 0.3847887325286865
┌ Info: iter 200
└   metric = 0.3801265645027161
┌ Info: initialization
└   metric = 0.5471089428663254
┌ Info: iter 25
└   metric = 0.21913841038942336
┌ Info: iter 50
└   metric = 0.13720423802733422
┌ Info: iter 75
└   metric = 0.11385027751326561
┌ Info: iter 100
└   metric = 0.10443447336554527
┌ Info: iter 125
└   metric = 0.09951980963349343
┌ Info: iter 150
└   metric = 0.09702852010726928
┌ Info: iter 175
└   metric = 0.09551732912659645
┌ Info: iter 200
└   metric = 0.094958426207304
┌ Info: initialization
└   metric = 0.2957647952437401
┌ Info: iter 25
└   metric = 0.07575521223247052
┌ Info: iter 50
└   metric = 0.055389644242823124
┌ Info: iter 75
└   metric = 0.04930419464595616
┌ Info: iter 100
└   metric = 0.04735164218582213
┌ Info: iter 125
└   metric = 0.04671690450981259
┌ Info: iter 150
└   metric = 0.04653070217464119
┌ Info: iter 175
└   metric = 0.046541841465514155
┌ Info: iter 200
└   metric = 0.04664113273145631
┌ Info: initialization
└   metric = 0.5254025399684906
┌ Info: iter 25
└   metric = 1.2444885614514352
┌ Info: iter 50
└   metric = 1.5074850124120713
┌ Info: iter 75
└   metric = 1.6780072042346001
┌ Info: iter 100
└   metric = 1.7726103961467743
┌ Info: iter 125
└   metric = 1.8351438862085343
┌ Info: iter 150
└   metric = 1.8794235858321189
┌ Info: iter 175
└   metric = 1.9026350170373916
┌ Info: iter 200
└   metric = 1.9192887452244758
┌ Info: initialization
└   metric = -1.7957830564654431
┌ Info: iter 25
└   metric = -0.5233324768813327
┌ Info: iter 50
└   metric = -0.3126774764340371
┌ Info: iter 75
└   metric = -0.1482080158177996
┌ Info: iter 100
└   metric = -0.08164310291409492
┌ Info: iter 125
└   metric = -0.04318209574557841
┌ Info: iter 150
└   metric = -0.03685651195701212
┌ Info: iter 175
└   metric = -0.03313629071228206
┌ Info: iter 200
└   metric = -0.041607066886499525
┌ Info: initialization
└   metric = 0.6875359496474266
┌ Info: iter 50
└   metric = 0.298640475012362
┌ Info: iter 100
└   metric = 0.2744265696126968
┌ Info: initialization
└   metric = 0.12692690002214477
┌ Info: iter 25
└   metric = 0.035449535256672104
┌ Info: iter 50
└   metric = 0.022091049771033867
┌ Info: iter 75
└   metric = 0.019839464080984897
┌ Info: iter 100
└   metric = 0.019345529151084194
┌ Info: initialization
└   metric = 0.12692690002214477
┌ Info: iter 25
└   metric = 0.03533317220291012
┌ Info: iter 50
└   metric = 0.021854105652548982
┌ Info: iter 75
└   metric = 0.019633157023992282
┌ Info: iter 100
└   metric = 0.01929916271276106
┌ Info: initialization
└   metric = 0.020358958927368376
┌ Info: iter 25
└   metric = 0.004361602189505604
┌ Info: iter 50
└   metric = 0.0013782550718356656
┌ Info: iter 75
└   metric = 0.000822369201089872
┌ Info: iter 100
└   metric = 0.0007169724630985339
┌ Info: iter 125
└   metric = 0.000697192498014724
┌ Info: iter 150
└   metric = 0.0006930728099176076
┌ Info: iter 175
└   metric = 0.0006917962010436209
┌ Info: iter 200
└   metric = 0.0006918942449952894
┌ Info: initialization
└   metric = 0.020358958927368376
┌ Info: iter 25
└   metric = 0.0024131638495896064
┌ Info: iter 50
└   metric = 0.0024127923751441054
┌ Info: iter 75
└   metric = 0.0024143452895525356
┌ Info: iter 100
└   metric = 0.0024144685438429506
┌ Info: iter 125
└   metric = 0.0024142454706221946
┌ Info: iter 150
└   metric = 0.00241333997505191
┌ Info: iter 175
└   metric = 0.0024134418835719505
┌ Info: iter 200
└   metric = 0.0024133667874534693
┌ Info: initialization
└   metric = 0.40619069431722166
┌ Info: iter 25
└   metric = 0.34405948795750735
┌ Info: iter 50
└   metric = 0.33176836168952284
┌ Info: iter 75
└   metric = 0.328082158215344
┌ Info: iter 100
└   metric = 0.3265756065798923
┌ Info: iter 125
└   metric = 0.32582493518106637
┌ Info: iter 150
└   metric = 0.3254002459323965
┌ Info: iter 175
└   metric = 0.32513588516507297
┌ Info: iter 200
└   metric = 0.3249636071003042
┌ Info: initialization
└   metric = 0.40619069431722166
┌ Info: iter 25
└   metric = 0.3523449128419161
┌ Info: iter 50
└   metric = 0.34380327036231756
┌ Info: iter 75
└   metric = 0.34201818084344265
┌ Info: iter 100
└   metric = 0.3415592436958104
┌ Info: iter 125
└   metric = 0.34141718253679576
┌ Info: iter 150
└   metric = 0.3413602010793984
┌ Info: iter 175
└   metric = 0.34133762077614666
┌ Info: iter 200
└   metric = 0.34132483863271773
[ Info: The following kwargs are not supported and will be ignored: [:metric].
┌ Info: initialization
└   metric = 1.4467687221169472
┌ Info: iter 25
└   metric = 2.3832271227240565
┌ Info: iter 50
└   metric = 2.996125996410847
┌ Info: iter 75
└   metric = 3.403247866272926
┌ Info: iter 100
└   metric = 3.639958354651928
┌ Info: iter 125
└   metric = 3.7699330707788468
┌ Info: iter 150
└   metric = 3.842245651423931
┌ Info: iter 175
└   metric = 3.8804836964011193
┌ Info: iter 200
└   metric = 3.891482799530029
┌ Info: initialization
└   metric = 1.4467687221169472
┌ Info: iter 25
└   metric = 2.6959541272521017
┌ Info: iter 50
└   metric = 2.696875432550907
┌ Info: iter 75
└   metric = 2.696397373497486
┌ Info: iter 100
└   metric = 2.696485609412193
┌ Info: iter 125
└   metric = 2.6961648224592207
┌ Info: iter 150
└   metric = 2.6968972423672675
┌ Info: iter 175
└   metric = 2.6965816232562063
┌ Info: iter 200
└   metric = 2.6968879861831665
┌ Info: initialization
└   metric = 0.006764594764525853
Precompiling packages...
   3184.9 ms  ✓ LogExpFunctions → LogExpFunctionsChainRulesCoreExt
   4202.0 ms  ✓ SpecialFunctions → SpecialFunctionsChainRulesCoreExt
  14692.9 ms  ✓ NNlib
   3839.6 ms  ✓ StatsFuns → StatsFunsChainRulesCoreExt
   1517.1 ms  ✓ StatsFuns → StatsFunsInverseFunctionsExt
   4856.7 ms  ✓ Distributions → DistributionsChainRulesCoreExt
   8743.9 ms  ✓ ScientificTypes
   3331.8 ms  ✓ NNlib → NNlibSpecialFunctionsExt
  24139.5 ms  ✓ MLUtils
   8208.3 ms  ✓ CategoricalDistributions
  21061.0 ms  ✓ StatisticalMeasuresBase
  18379.5 ms  ✓ MLJBase
  12 dependencies successfully precompiled in 117 seconds. 134 already precompiled.
Precompiling packages...
  12418.2 ms  ✓ BangBang → BangBangDataFramesExt
  1 dependency successfully precompiled in 13 seconds. 47 already precompiled.
Precompiling packages...
   7649.6 ms  ✓ Transducers → TransducersDataFramesExt
  1 dependency successfully precompiled in 8 seconds. 63 already precompiled.
Precompiling packages...
  19468.7 ms  ✓ MLJTestInterface
  1 dependency successfully precompiled in 21 seconds. 163 already precompiled.
┌ Info: Training machine(EvoTreeRegressor
│  - loss: logloss
│  - metric: logloss
│  - nrounds: 10
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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
│  - bagging_size: 1
│  - 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  14m00.5s
     Testing EvoTrees tests passed 

Testing completed after 865.09s

PkgEval succeeded after 1308.51s