Package evaluation of CatBoost on Julia 1.11.4 (a71dd056e0*) started at 2025-04-08T11:49:20.135 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 8.09s ################################################################################ # Installation # Installing CatBoost... Resolving package versions... Updating `~/.julia/environments/v1.11/Project.toml` [e2e10f9a] + CatBoost v0.3.6 Updating `~/.julia/environments/v1.11/Manifest.toml` [e2e10f9a] + CatBoost v0.3.6 [324d7699] + CategoricalArrays v0.10.8 [992eb4ea] + CondaPkg v0.2.27 [9a962f9c] + DataAPI v1.16.0 [e2d170a0] + DataValueInterfaces v1.0.0 [82899510] + IteratorInterfaceExtensions v1.0.0 [692b3bcd] + JLLWrappers v1.7.0 [0f8b85d8] + JSON3 v1.14.2 [e80e1ace] + MLJModelInterface v1.11.0 [1914dd2f] + MacroTools v0.5.15 [0b3b1443] + MicroMamba v0.1.14 [e1d29d7a] + Missings v1.2.0 [bac558e1] + OrderedCollections v1.8.0 [69de0a69] + Parsers v2.8.1 [fa939f87] + Pidfile v1.3.0 ⌅ [aea7be01] + PrecompileTools v1.2.1 [21216c6a] + Preferences v1.4.3 [6099a3de] + PythonCall v0.9.24 [ae029012] + Requires v1.3.1 [30f210dd] + ScientificTypesBase v3.0.0 [6c6a2e73] + Scratch v1.2.1 [64bff920] + StatisticalTraits v3.4.0 [10745b16] + Statistics v1.11.1 [856f2bd8] + StructTypes v1.11.0 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.0 [e17b2a0c] + UnsafePointers v1.0.0 [f8abcde7] + micromamba_jll v1.5.8+0 [4d7b5844] + pixi_jll v0.41.3+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 [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 [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 [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 4.13s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 92.49s ################################################################################ # Testing # Testing CatBoost Status `/tmp/jl_PxACEU/Project.toml` [4c88cf16] Aqua v0.8.11 [e2e10f9a] CatBoost v0.3.6 [324d7699] CategoricalArrays v0.10.8 [a93c6f00] DataFrames v1.7.0 ⌃ [a7f614a8] MLJBase v1.7.0 [e80e1ace] MLJModelInterface v1.11.0 [72560011] MLJTestInterface v0.2.8 [03970b2e] MLJTuning v0.8.8 [bac558e1] OrderedCollections v1.8.0 [6099a3de] PythonCall v0.9.24 ⌅ [a19d573c] StatisticalMeasures v0.1.7 [10745b16] Statistics v1.11.1 [bd369af6] Tables v1.12.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_PxACEU/Manifest.toml` [7d9f7c33] Accessors v0.1.42 [79e6a3ab] Adapt v4.3.0 [66dad0bd] AliasTables v1.1.3 [4c88cf16] Aqua v0.8.11 [dce04be8] ArgCheck v2.5.0 [a9b6321e] Atomix v1.1.1 [198e06fe] BangBang v0.4.4 [9718e550] Baselet v0.1.1 [e2e10f9a] CatBoost v0.3.6 [324d7699] CategoricalArrays v0.10.8 [af321ab8] CategoricalDistributions v0.1.15 [d360d2e6] ChainRulesCore v1.25.1 [3da002f7] ColorTypes v0.12.1 [34da2185] Compat v4.16.0 [a33af91c] CompositionsBase v0.1.2 [ed09eef8] ComputationalResources v0.3.2 [992eb4ea] CondaPkg v0.2.27 [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 [cc61a311] FLoops v0.2.2 [b9860ae5] FLoopsBase v0.1.1 [1a297f60] FillArrays v1.13.0 [53c48c17] FixedPointNumbers v0.8.5 [46192b85] GPUArraysCore v0.2.0 [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 [82899510] IteratorInterfaceExtensions v1.0.0 [692b3bcd] JLLWrappers v1.7.0 [0f8b85d8] JSON3 v1.14.2 [b14d175d] JuliaVariables v0.2.4 [63c18a36] KernelAbstractions v0.9.34 [b964fa9f] LaTeXStrings v1.4.0 [a5e1c1ea] LatinHypercubeSampling v1.9.0 ⌅ [92ad9a40] LearnAPI v0.1.0 [2ab3a3ac] LogExpFunctions v0.3.29 [c2834f40] MLCore v1.0.0 ⌃ [a7f614a8] MLJBase v1.7.0 [e80e1ace] MLJModelInterface v1.11.0 [72560011] MLJTestInterface v0.2.8 [03970b2e] MLJTuning v0.8.8 [d8e11817] MLStyle v0.4.17 [f1d291b0] MLUtils v0.4.8 [1914dd2f] MacroTools v0.5.15 [128add7d] MicroCollections v0.2.0 [0b3b1443] MicroMamba v0.1.14 [e1d29d7a] Missings v1.2.0 [872c559c] NNlib v0.9.30 [71a1bf82] NameResolution v0.1.5 [bac558e1] OrderedCollections v1.8.0 [90014a1f] PDMats v0.11.33 [d96e819e] Parameters v0.12.3 [69de0a69] Parsers v2.8.1 [fa939f87] Pidfile v1.3.0 [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 [6099a3de] PythonCall v0.9.24 [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 [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 [860ef19b] StableRNGs v1.0.2 [90137ffa] StaticArrays v1.9.13 [1e83bf80] StaticArraysCore v1.4.3 ⌅ [a19d573c] StatisticalMeasures v0.1.7 [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 [856f2bd8] StructTypes v1.11.0 [3783bdb8] TableTraits v1.0.1 [bd369af6] Tables v1.12.0 [28d57a85] Transducers v0.4.84 [3a884ed6] UnPack v1.0.2 [013be700] UnsafeAtomics v0.3.0 [e17b2a0c] UnsafePointers v1.0.0 [efe28fd5] OpenSpecFun_jll v0.5.6+0 [f50d1b31] Rmath_jll v0.5.1+0 [f8abcde7] micromamba_jll v1.5.8+0 [4d7b5844] pixi_jll v0.41.3+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 ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. Testing Running tests... Precompiling MLJBase... 1544.3 ms ✓ StaticArrays → StaticArraysChainRulesCoreExt 1980.0 ms ✓ CategoricalArrays → CategoricalArraysRecipesBaseExt 4209.8 ms ✓ SpecialFunctions → SpecialFunctionsChainRulesCoreExt 1388.8 ms ✓ StatsFuns → StatsFunsInverseFunctionsExt 3938.7 ms ✓ StatsFuns → StatsFunsChainRulesCoreExt 3531.5 ms ✓ Distributions → DistributionsChainRulesCoreExt 7802.0 ms ✓ ScientificTypes 24269.7 ms ✓ NNlib 7234.1 ms ✓ CategoricalDistributions 2274.3 ms ✓ NNlib → NNlibSpecialFunctionsExt 28134.0 ms ✓ MLUtils 15019.7 ms ✓ StatisticalMeasuresBase 16428.7 ms ✓ MLJBase 13 dependencies successfully precompiled in 120 seconds. 130 already precompiled. Precompiling BangBangDataFramesExt... 4235.4 ms ✓ BangBang → BangBangDataFramesExt 1 dependency successfully precompiled in 5 seconds. 45 already precompiled. Precompiling TransducersDataFramesExt... 4198.1 ms ✓ Transducers → TransducersDataFramesExt 1 dependency successfully precompiled in 5 seconds. 61 already precompiled. Precompiling MLJTestInterface... 12823.3 ms ✓ MLJTestInterface 1 dependency successfully precompiled in 14 seconds. 158 already precompiled. Precompiling MLJTuning... 1992.7 ms ✓ LatinHypercubeSampling 11024.2 ms ✓ MLJTuning 2 dependencies successfully precompiled in 14 seconds. 144 already precompiled. Precompiling PythonCall... 23786.4 ms ✓ PythonCall 1 dependency successfully precompiled in 24 seconds. 49 already precompiled. CondaPkg Found dependencies: /home/pkgeval/.julia/packages/CatBoost/9RVr2/CondaPkg.toml CondaPkg Found dependencies: /home/pkgeval/.julia/packages/PythonCall/WMWY0/CondaPkg.toml CondaPkg Resolving changes + catboost + libstdcxx-ng + python CondaPkg Initialising pixi │ /home/pkgeval/.julia/artifacts/cefba4912c2b400756d043a2563ef77a0088866b/bin/pixi │ init │ --format pixi └ /tmp/jl_PxACEU/.CondaPkg ✔ Created /tmp/jl_PxACEU/.CondaPkg/pixi.toml CondaPkg Wrote /tmp/jl_PxACEU/.CondaPkg/pixi.toml │ [dependencies] │ libstdcxx-ng = ">=3.4,<13.0" │ catboost = ">=1.1" │ │ [dependencies.python] │ channel = "conda-forge" │ build = "*cpython*" │ version = ">=3.8,<4" │ │ [project] │ name = ".CondaPkg" │ platforms = ["linux-64"] │ channels = ["conda-forge"] │ channel-priority = "strict" └ description = "automatically generated by CondaPkg.jl" CondaPkg Installing packages │ /home/pkgeval/.julia/artifacts/cefba4912c2b400756d043a2563ef77a0088866b/bin/pixi │ install └ --manifest-path /tmp/jl_PxACEU/.CondaPkg/pixi.toml ✔ The default environment has been installed. Precompiling CategoricalArraysStructTypesExt... 970.1 ms ✓ CategoricalArrays → CategoricalArraysStructTypesExt 1 dependency successfully precompiled in 1 seconds. 11 already precompiled. Precompiling StatisticalMeasures... 43269.9 ms ✓ StatisticalMeasures 7801.9 ms ✓ StatisticalMeasures → ScientificTypesExt 2 dependencies successfully precompiled in 52 seconds. 134 already precompiled. Precompiling DefaultMeasuresExt... 7598.7 ms ✓ MLJBase → DefaultMeasuresExt 1 dependency successfully precompiled in 11 seconds. 145 already precompiled. Precompiling CatBoost... 16490.8 ms ✓ CatBoost 1 dependency successfully precompiled in 17 seconds. 58 already precompiled. TBB Warning: The number of workers is currently limited to 0. The request for 127 workers is ignored. Further requests for more workers will be silently ignored until the limit changes. (iterations = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99], test-Logloss-mean = [0.6890134793905154, 0.6853401876417918, 0.6858578015175667, 0.6859746203358953, 0.6866132789214381, 0.6876509449487843, 0.6853429724756974, 0.6849086924215081, 0.6819307616913378, 0.6835469902936051, 0.6819821409479003, 0.680767362188175, 0.6808331535997788, 0.682720772275654, 0.682899332778051, 0.6850429386530708, 0.6874346244177201, 0.6900586247688089, 0.692899950477441, 0.6959887141679293, 0.6991426359564759, 0.7025186503465161, 0.7016230580405801, 0.705175716161069, 0.7033744527707794, 0.707058515492332, 0.7076309444600962, 0.7083692614229988, 0.7092636191338735, 0.701896448671518, 0.7054698657826535, 0.7064964955584907, 0.7101808354217923, 0.7113723784290522, 0.7102983598280914, 0.7142487135737103, 0.7182732350125578, 0.7223660634709698, 0.7223718130903916, 0.7265209865313986, 0.7265265496733806, 0.727972774003325, 0.7295006499165919, 0.7322663789876686, 0.7364540067911047, 0.7402735530806708, 0.744133466883486, 0.7457593616918756, 0.7499469181472066, 0.7492439180294934, 0.7485897950459234, 0.752750188729334, 0.7565642633711924, 0.7607330989825964, 0.7559895922591389, 0.7597954571130741, 0.7616155475608997, 0.7657248020841703, 0.7681286666848606, 0.7699703626548378, 0.7718444066079488, 0.7755790182940308, 0.7795924677055551, 0.7819505302775931, 0.7856899043294352, 0.7883078800493133, 0.7835458448882879, 0.7874978957238454, 0.7911972909596655, 0.7951258633184934, 0.7988050383357028, 0.8005575531481103, 0.8042023233290929, 0.8064930928179515, 0.8067190313644551, 0.8103439168650179, 0.8139655027071647, 0.8157022784200483, 0.8174518940767723, 0.8198261763933019, 0.8235006843454847, 0.8239231418876148, 0.8275644486933313, 0.8310250697880568, 0.8327424945303024, 0.8363149422449258, 0.8382768564316675, 0.8416750889158854, 0.843644436013581, 0.8471504401206937, 0.8505173292162911, 0.852641199449382, 0.8546056601608976, 0.8580446737096594, 0.8596475870349501, 0.8630432890067329, 0.8663210431949637, 0.8696811131140322, 0.8730301394339282, 0.8745686894267508], test-Logloss-std = [0.005904348162409469, 0.011887046445524758, 0.012817985897026202, 0.02364008723876494, 0.024923113328054598, 0.02640451132836346, 0.03332986864740051, 0.03256395799675069, 0.03808518584365143, 0.04006856310736657, 0.04715788049384728, 0.05431675213955318, 0.0541243018305137, 0.057411052281829855, 0.05711505057849913, 0.060483034388504435, 0.0639446331510014, 0.06748810726331592, 0.07110247623999655, 0.07471476967607188, 0.07855411355289016, 0.08237157265323129, 0.08963712350913272, 0.09362619116534872, 0.09928404531401173, 0.10338859242247707, 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0.3185957247422203, 0.32289680617823996, 0.32714217966077863, 0.3339922466306673, 0.3407629483381396, 0.3429191944722248, 0.3468709029342637, 0.35164978521099227, 0.35555223122926277, 0.3596481481937902, 0.3661472121778673, 0.3699607749339723, 0.37193265326623703, 0.37589532610288257, 0.3777979834186397, 0.38151132605376037, 0.38535976825927076, 0.3874140815438524, 0.38920779387434984, 0.39282370766265395, 0.3989753583464152, 0.4025310130348208, 0.4061931751086288, 0.40967896422705313, 0.4131207646111536, 0.41906373002193276], train-Logloss-mean = [0.6815491733268604, 0.6608940683984985, 0.6410687877714474, 0.6296561368197743, 0.6129767409103326, 0.5969063874247631, 0.579577207630156, 0.57041141424767, 0.5614660271877973, 0.5471905824123389, 0.5317517402815294, 0.5169217580315058, 0.511209455270411, 0.49714021797969565, 0.4892222124393306, 0.4759828149485869, 0.46325704956664826, 0.4510200051415937, 0.44054875780740055, 0.4291673299032665, 0.4182163509586773, 0.4076744913519864, 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0.17041242942376822, 0.16784421399974944, 0.1653400308801622, 0.1631565460253101, 0.16102235475144072, 0.15868756729861283, 0.15641052929941965, 0.15443778834716662, 0.1522631638079102, 0.15060451836806243, 0.148519815054266, 0.14669974457401389, 0.1447079209674566, 0.14276229274036095, 0.14086293937298178, 0.13900616848869202, 0.1373847667518494, 0.13560747606148807, 0.1340537719811496, 0.1323525795676872, 0.13068752961698143, 0.1294109287373747, 0.12798169902291914, 0.1265836043769047, 0.12504373862289547, 0.12370230544386686, 0.12222405006036578, 0.12077680871831711, 0.11936149737281247, 0.11797435010866526], train-Logloss-std = [0.007306810142071458, 0.0010614347583951312, 0.004738183624066662, 0.0006564277373835488, 0.0020720182895939752, 0.0046101471623885126, 0.009559442522879866, 0.0035784776924582683, 0.002105914894214375, 0.00030987675498216234, 0.0049420083730193085, 0.00924368983939214, 0.0011720025095939893, 0.005415843115938139, 0.0014353547509606513, 0.005451357791323996, 0.009185055606679886, 0.012651004856734926, 0.014033495524326046, 0.017091959502224936, 0.019927762929410103, 0.022551914703446266, 0.0218943437599772, 0.02270559094669801, 0.019059947526309424, 0.019912105428569093, 0.020689094191550586, 0.02282484131206336, 0.023423539487076962, 0.02412012744911497, 0.02590999301111185, 0.027567073927389153, 0.029096683331820167, 0.030510540377933347, 0.027584680676123383, 0.02895180238398244, 0.02915598025427063, 0.03036726817701664, 0.026582063893322717, 0.02780431175995317, 0.028067740633969926, 0.029149705206277198, 0.030153383038470826, 0.03027206761942065, 0.03113738300869108, 0.031933283018266874, 0.03189288827599285, 0.032599037928555716, 0.03250909082379197, 0.030494843221085588, 0.02853766217932235, 0.029237249809995217, 0.02988790254181824, 0.030481902052973478, 0.028826763272332353, 0.029400989168406888, 0.02931063107203074, 0.02981923772494438, 0.02915600578138202, 0.029619182966684848, 0.030062103975796794, 0.030468638213309005, 0.030836463612308566, 0.030194844112816397, 0.030530303440738833, 0.029901882160561378, 0.029770508842852986, 0.03006045386284525, 0.03032290331591932, 0.030558058932816334, 0.030772129538254728, 0.030963192152583568, 0.03113160852321852, 0.03092021443319317, 0.03070577447003626, 0.030839810586596014, 0.030957156546297656, 0.030704631686127432, 0.03080098111945408, 0.030230150762261855, 0.030316005392388018, 0.030085849088196556, 0.030155497166807658, 0.030212382770070385, 0.03025941753231098, 0.03029405770579478, 0.030050531711449627, 0.0300738696696053, 0.029827053843499783, 0.02984206002477127, 0.029846445629741647, 0.029346156949494065, 0.029108701236876415, 0.028867253394289284, 0.028868752588543625, 0.028628485138370817, 0.028623154394195084, 0.02861117883920849, 0.028595498875573246, 0.028572368202479045],) Data dims: (10000, 136) Num queries: 10000 Training with: PyDict{Py, Py} with 5 entries: 'random_seed' => 314159 'iterations' => 10 'custom_metric' => Julia: 3-element Vector{String}: "MAP:top=10" "PrecisionAt:top=10" "RecallAt:top=10" 'loss_function' => 'RMSE' 'verbose' => False l : e v : a Test Summary: | Pass Total Time Python Wrapper | 3 3 1m23.1s WARNING: replacing module Binary. [ Info: Training machine(CatBoostClassifier(iterations = 2, …), …). [ Info: Training machine(CatBoostClassifier(iterations = 2, …), …). WARNING: replacing module Regression. [ Info: Training machine(CatBoostRegressor(iterations = 2, …), …). [ Info: Training machine(CatBoostClassifier(iterations = 5, …), …). ┌ Warning: The number and/or types of data arguments do not match what the specified model │ supports. Suppress this type check by specifying `scitype_check_level=0`. │ │ Run `@doc CatBoost.CatBoostClassifier` to learn more about your model's requirements. │ │ Commonly, but non exclusively, supervised models are constructed using the syntax │ `machine(model, X, y)` or `machine(model, X, y, w)` while most other models are │ constructed with `machine(model, X)`. Here `X` are features, `y` a target, and `w` │ sample or class weights. │ │ In general, data in `machine(model, data...)` is expected to satisfy │ │ scitype(data) <: MLJ.fit_data_scitype(model) │ │ In the present case: │ │ scitype(data) = Tuple{Table{AbstractVector{Count}}, AbstractVector{Count}} │ │ fit_data_scitype(model) = Tuple{Union{Table{<:Union{AbstractVector{<:Continuous}, AbstractVector{<:Count}, AbstractVector{<:OrderedFactor}, AbstractVector{<:ScientificTypesBase.Multiclass}}}, AbstractMatrix{Continuous}}, AbstractVector{<:Finite}} └ @ MLJBase ~/.julia/packages/MLJBase/7nGJF/src/machines.jl:237 [ Info: Training machine(CatBoostClassifier(iterations = 5, …), …). UnivariateFinite{ScientificTypesBase.Multiclass{1}, Int64, UInt32, Float64}[UnivariateFinite{ScientificTypesBase.Multiclass{1}}(0=>1.0), UnivariateFinite{ScientificTypesBase.Multiclass{1}}(0=>1.0), UnivariateFinite{ScientificTypesBase.Multiclass{1}}(0=>1.0), UnivariateFinite{ScientificTypesBase.Multiclass{1}}(0=>1.0)] CategoricalArrays.CategoricalValue{Int64, UInt32}[0, 0, 0, 0] [ Info: Training machine(CatBoostRegressor(iterations = 5, …), …). Test Summary: | Pass Total Time MLJ Interface | 9 9 3m12.5s Test Summary: | Pass Total Time Method ambiguity | 1 1 21.4s Test Summary: | Pass Total Time Unbound type parameters | 1 1 0.3s Test Summary: | Pass Total Time Undefined exports | 1 1 0.0s Test Summary: | Pass Total Time Compare Project.toml and test/Project.toml | 1 1 0.0s Test Summary: | Pass Total Time Stale dependencies | 1 1 26.4s Test Summary: | Pass Total Time Compat bounds | 4 4 0.8s Test Summary: | Pass Total Time Piracy | 1 1 0.4s Test Summary: | Pass Total Time Persistent tasks | 1 1 42.3s 0: learn: 0.5799547 total: 258us remaining: 258us 1: learn: 0.4935526 total: 433us remaining: 0us Training on fold [0/2] bestTest = 0.5738373179 bestIteration = 84 Training on fold [1/2] bestTest = 0.693188484 bestIteration = 0 0: learn: 0.9417331 total: 1.45ms remaining: 13.1ms 1: learn: 0.8421839 total: 1.63ms remaining: 6.52ms 2: learn: 0.6597822 total: 1.75ms remaining: 4.07ms 3: learn: 0.6028493 total: 1.84ms remaining: 2.77ms 4: learn: 0.4900112 total: 1.94ms remaining: 1.94ms 5: learn: 0.4076408 total: 2.04ms remaining: 1.36ms 6: learn: 0.3458205 total: 2.13ms remaining: 912us 7: learn: 0.2982687 total: 2.22ms remaining: 555us 8: learn: 0.2608927 total: 2.31ms remaining: 256us 9: learn: 0.2309514 total: 2.4ms remaining: 0us Testing CatBoost tests passed Testing completed after 698.83s PkgEval succeeded after 848.54s