Package evaluation to test SoleModels on Julia 1.14.0-DEV.2291 (26145852c4*) started at 2026-06-08T22:05:22.740 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Activating project at `~/.julia/environments/v1.14` Set-up completed after 17.75s ################################################################################ # Installation # Installing SoleModels... Resolving package versions... Installed Indexing ──────────────────── v1.1.1 Installed URIs ──────────────────────── v1.6.1 Installed Rmath_jll ─────────────────── v0.5.1+0 Installed MacroTools ────────────────── v0.5.16 Installed catch22_jll ───────────────── v0.5.0+0 Installed FilePathsBase ─────────────── v0.9.24 Installed AbstractTrees ─────────────── v0.4.5 Installed DataStructures ────────────── v0.18.22 Installed SoleBase ──────────────────── v0.13.4 Installed FillArrays ────────────────── v1.16.0 Installed SoleModels ────────────────── v0.10.7 Installed ConstructionBase ──────────── v1.6.0 Installed DelimitedFiles ────────────── v1.9.1 Installed ArnoldiMethod ─────────────── v0.4.0 Installed AliasTables ───────────────── v1.1.3 Installed TableShowUtils ────────────── v0.2.7 Installed InlineStrings ─────────────── v1.4.5 Installed StatsBase ─────────────────── v0.34.11 Installed Extents ───────────────────── v0.1.6 Installed TimeseriesFeatures ────────── v0.6.1 Installed HypergeometricFunctions ───── v0.3.28 Installed ScientificTypes ───────────── v3.3.0 Installed ZipFile ───────────────────── v0.10.1 Installed ConcurrentUtilities ───────── v2.5.1 Installed CodecZlib ─────────────────── v0.7.8 Installed ExceptionUnwrapping ───────── v0.1.11 Installed OrderedCollections ────────── v1.8.2 Installed TranscodingStreams ────────── v0.11.3 Installed CSV ───────────────────────── v0.10.16 Installed Compat ────────────────────── v4.18.1 Installed IteratorInterfaceExtensions ─ v1.0.0 Installed ProgressLogging ───────────── v0.1.6 Installed DataAPI ───────────────────── v1.16.0 Installed Combinatorics ─────────────── v1.1.0 Installed SoleData ──────────────────── v0.16.8 Installed Statistics ────────────────── v1.11.1 Installed InvertedIndices ───────────── v1.3.1 Installed DataValueInterfaces ───────── v1.0.0 Installed StatsAPI ──────────────────── v1.8.0 Installed SentinelArrays ────────────── v1.4.10 Installed MbedTLS ───────────────────── v1.1.10 Installed Catch22 ───────────────────── v0.7.0 Installed OpenSSL ───────────────────── v1.6.1 Installed ProgressMeter ─────────────── v1.11.0 Installed PrecompileTools ───────────── v1.3.4 Installed Revise ────────────────────── v3.14.5 Installed StaticArrays ──────────────── v1.9.18 Installed Compiler ──────────────────── v0.1.1 Installed LoggingExtras ─────────────── v1.2.0 Installed TableTraitsUtils ──────────── v1.0.2 Installed StaticArraysCore ──────────── v1.4.4 Installed StructUtils ───────────────── v2.8.2 Installed CodeTracking ──────────────── v3.0.2 Installed IrrationalConstants ───────── v0.2.6 Installed QuadGK ────────────────────── v2.11.3 Installed DimensionalData ───────────── v0.29.27 Installed StringManipulation ────────── v0.4.4 Installed MultiData ─────────────────── v0.1.4 Installed ColorTypes ────────────────── v0.12.1 Installed HTTP ──────────────────────── v1.11.0 Installed Requires ──────────────────── v1.3.1 Installed DataValues ────────────────── v0.4.13 Installed OpenSpecFun_jll ───────────── v0.5.6+0 Installed LoweredCodeUtils ──────────── v3.5.3 Installed FunctionWrappers ──────────── v1.1.3 Installed LogExpFunctions ───────────── v0.3.29 Installed SimpleTraits ──────────────── v0.9.6 Installed BitFlags ──────────────────── v0.1.10 Installed IterableTables ────────────── v1.0.0 Installed Interfaces ────────────────── v0.3.2 Installed JuliaInterpreter ──────────── v0.10.12 Installed Parsers ───────────────────── v2.8.5 Installed JSON ──────────────────────── v1.6.1 Installed Distributions ─────────────── v0.25.126 Installed PrettyTables ──────────────── v3.3.2 Installed ThreadSafeDicts ───────────── v0.1.6 Installed Rmath ─────────────────────── v0.9.0 Installed Tables ────────────────────── v1.12.1 Installed StatsFuns ─────────────────── v2.0.1 Installed PtrArrays ─────────────────── v1.4.0 Installed SpecialFunctions ──────────── v2.8.0 Installed Discretizers ──────────────── v3.2.4 Installed Reexport ──────────────────── v1.2.2 Installed DataFrames ────────────────── v1.8.2 Installed IntervalSets ──────────────── v0.7.14 Installed Missings ──────────────────── v1.2.0 Installed FixedPointNumbers ─────────── v0.8.6 Installed ScientificTypesBase ───────── v3.1.0 Installed SimpleBufferStream ────────── v1.2.0 Installed Preferences ───────────────── v1.5.2 Installed PooledArrays ──────────────── v1.4.3 Installed TableTraits ───────────────── v1.0.1 Installed LaTeXStrings ──────────────── v1.4.0 Installed SortingAlgorithms ─────────── v1.2.2 Installed WeakRefStrings ────────────── v1.4.3 Installed JLLWrappers ───────────────── v1.8.0 Installed Query ─────────────────────── v1.1.0 Installed MbedTLS_jll ───────────────── v2.28.1010+0 Installed PDMats ────────────────────── v0.11.37 Installed UniqueVectors ─────────────── v1.2.0 Installed Crayons ───────────────────── v4.1.1 Installed SoleLogics ────────────────── v0.13.7 Installed QueryOperators ────────────── v1.0.1 Installed IterTools ─────────────────── v1.10.0 Installed Graphs ────────────────────── v1.13.1 Installed Lazy ──────────────────────── v0.15.1 Installed WorkerUtilities ───────────── v1.6.1 Installed StatisticalTraits ─────────── v3.5.0 Installed CategoricalArrays ─────────── v1.1.1 Installed Dictionaries ──────────────── v0.4.6 Installed DocStringExtensions ───────── v0.9.5 Installed Inflate ───────────────────── v0.1.5 Installed MLJModelInterface ─────────── v1.12.1 Installing 5 artifacts Installed artifact Rmath 121.9 KiB Installed artifact OpenSpecFun 194.9 KiB Installed artifact catch22 97.8 KiB Installed artifact MbedTLS 2.2 MiB Installed artifact testfiles 6.2 MiB Updating `~/.julia/environments/v1.14/Project.toml` [4249d9c7] + SoleModels v0.10.7 Updating `~/.julia/environments/v1.14/Manifest.toml` [1520ce14] + AbstractTrees v0.4.5 [66dad0bd] + AliasTables v1.1.3 [ec485272] + ArnoldiMethod v0.4.0 [d1d4a3ce] + BitFlags v0.1.10 [336ed68f] + CSV v0.10.16 [acdeb78f] + Catch22 v0.7.0 [324d7699] + CategoricalArrays v1.1.1 [da1fd8a2] + CodeTracking v3.0.2 [944b1d66] + CodecZlib v0.7.8 [3da002f7] + ColorTypes v0.12.1 [861a8166] + Combinatorics v1.1.0 [34da2185] + Compat v4.18.1 [807dbc54] + Compiler v0.1.1 [f0e56b4a] + ConcurrentUtilities v2.5.1 [187b0558] + ConstructionBase v1.6.0 [a8cc5b0e] + Crayons v4.1.1 [9a962f9c] + DataAPI v1.16.0 [a93c6f00] + DataFrames v1.8.2 ⌅ [864edb3b] + DataStructures v0.18.22 [e2d170a0] + DataValueInterfaces v1.0.0 [e7dc6d0d] + DataValues v0.4.13 [8bb1440f] + DelimitedFiles v1.9.1 [85a47980] + Dictionaries v0.4.6 ⌅ [0703355e] + DimensionalData v0.29.27 [6e83dbb3] + Discretizers v3.2.4 [31c24e10] + Distributions v0.25.126 [ffbed154] + DocStringExtensions v0.9.5 [460bff9d] + ExceptionUnwrapping v0.1.11 [411431e0] + Extents v0.1.6 [48062228] + FilePathsBase v0.9.24 [1a297f60] + FillArrays v1.16.0 ⌅ [53c48c17] + FixedPointNumbers v0.8.6 [069b7b12] + FunctionWrappers v1.1.3 ⌃ [86223c79] + Graphs v1.13.1 ⌅ [cd3eb016] + HTTP v1.11.0 [34004b35] + HypergeometricFunctions v0.3.28 [313cdc1a] + Indexing v1.1.1 [d25df0c9] + Inflate v0.1.5 [842dd82b] + InlineStrings v1.4.5 [85a1e053] + Interfaces v0.3.2 [8197267c] + IntervalSets v0.7.14 [41ab1584] + InvertedIndices v1.3.1 [92d709cd] + IrrationalConstants v0.2.6 [c8e1da08] + IterTools v1.10.0 [1c8ee90f] + IterableTables v1.0.0 [82899510] + IteratorInterfaceExtensions v1.0.0 [692b3bcd] + JLLWrappers v1.8.0 [682c06a0] + JSON v1.6.1 [aa1ae85d] + JuliaInterpreter v0.10.12 [b964fa9f] + LaTeXStrings v1.4.0 [50d2b5c4] + Lazy v0.15.1 ⌅ [2ab3a3ac] + LogExpFunctions v0.3.29 [e6f89c97] + LoggingExtras v1.2.0 [6f1432cf] + LoweredCodeUtils v3.5.3 [e80e1ace] + MLJModelInterface v1.12.1 [1914dd2f] + MacroTools v0.5.16 [739be429] + MbedTLS v1.1.10 [e1d29d7a] + Missings v1.2.0 [8cc5100c] + MultiData v0.1.4 [4d8831e6] + OpenSSL v1.6.1 ⌅ [bac558e1] + OrderedCollections v1.8.2 [90014a1f] + PDMats v0.11.37 [69de0a69] + Parsers v2.8.5 [2dfb63ee] + PooledArrays v1.4.3 [aea7be01] + PrecompileTools v1.3.4 [21216c6a] + Preferences v1.5.2 [08abe8d2] + PrettyTables v3.3.2 [33c8b6b6] + ProgressLogging v0.1.6 [92933f4c] + ProgressMeter v1.11.0 [43287f4e] + PtrArrays v1.4.0 [1fd47b50] + QuadGK v2.11.3 [1a8c2f83] + Query v1.1.0 [2aef5ad7] + QueryOperators v1.0.1 [189a3867] + Reexport v1.2.2 [ae029012] + Requires v1.3.1 [295af30f] + Revise v3.14.5 [79098fc4] + Rmath v0.9.0 [321657f4] + ScientificTypes v3.3.0 [30f210dd] + ScientificTypesBase v3.1.0 [91c51154] + SentinelArrays v1.4.10 [777ac1f9] + SimpleBufferStream v1.2.0 [699a6c99] + SimpleTraits v0.9.6 [4475fa32] + SoleBase v0.13.4 [123f1ae1] + SoleData v0.16.8 [b002da8f] + SoleLogics v0.13.7 [4249d9c7] + SoleModels v0.10.7 [a2af1166] + SortingAlgorithms v1.2.2 [276daf66] + SpecialFunctions v2.8.0 [90137ffa] + StaticArrays v1.9.18 [1e83bf80] + StaticArraysCore v1.4.4 [64bff920] + StatisticalTraits v3.5.0 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.8.0 [2913bbd2] + StatsBase v0.34.11 [4c63d2b9] + StatsFuns v2.0.1 [892a3eda] + StringManipulation v0.4.4 [ec057cc2] + StructUtils v2.8.2 [5e66a065] + TableShowUtils v0.2.7 [3783bdb8] + TableTraits v1.0.1 [382cd787] + TableTraitsUtils v1.0.2 [bd369af6] + Tables v1.12.1 [4239201d] + ThreadSafeDicts v0.1.6 ⌅ [f3112013] + TimeseriesFeatures v0.6.1 [3bb67fe8] + TranscodingStreams v0.11.3 [5c2747f8] + URIs v1.6.1 [2fbcfb34] + UniqueVectors v1.2.0 [ea10d353] + WeakRefStrings v1.4.3 [76eceee3] + WorkerUtilities v1.6.1 [a5390f91] + ZipFile v0.10.1 [c8ffd9c3] + MbedTLS_jll v2.28.1010+0 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [f50d1b31] + Rmath_jll v0.5.1+0 [8a07c0c5] + catch22_jll v0.5.0+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 v1.13.0 [4af54fe1] + LazyArtifacts v1.11.0 [b27032c2] + LibCURL v1.0.0 [76f85450] + LibGit2 v1.11.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.14.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [a63ad114] + Mmap v1.11.0 [ca575930] + NetworkOptions v1.3.0 [44cfe95a] + Pkg v1.14.0 [de0858da] + Printf v1.11.0 [3fa0cd96] + REPL v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v1.13.0 [9e88b42a] + Serialization v1.11.0 [1a1011a3] + SharedArrays v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.13.0 [f489334b] + StyledStrings v1.13.0 [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 v1.5.2+0 [deac9b47] + LibCURL_jll v8.20.0+1 [e37daf67] + LibGit2_jll v1.9.4+0 [29816b5a] + LibSSH2_jll v1.11.101+0 [14a3606d] + MozillaCACerts_jll v2026.5.14 [4536629a] + OpenBLAS_jll v0.3.33+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.6+0 [efcefdf7] + PCRE2_jll v10.47.0+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.2+0 [3161d3a3] + Zstd_jll v1.5.7+1 [8e850b90] + libblastrampoline_jll v5.15.0+0 [8e850ede] + nghttp2_jll v1.69.0+0 [3f19e933] + p7zip_jll v17.8.0+0 Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m` Installation completed after 13.62s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling project... 5.1 s ✓ TestEnv 1 dependency successfully precompiled in 5 seconds. 27 already precompiled. Precompiling package dependencies... Precompiling project... 4.6 s ✓ MacroTools 1.6 s ✓ InlineStrings 0.6 s ✓ Reexport 1.0 s ✓ ConstructionBase 2.0 s ✓ IrrationalConstants 0.6 s ✓ PrettyPrint 0.5 s ✓ DataValueInterfaces 0.7 s ✓ StatsAPI 1.2 s ✓ Calculus 1.0 s ✓ IterTools 0.9 s ✓ IntervalSets 0.6 s ✓ CEnum 0.6 s ✓ Indexing 2.3 s ✓ Combinatorics 0.7 s ✓ Inflate 0.6 s ✓ ArgCheck 1.0 s ✓ TranscodingStreams 0.6 s ✓ LaTeXStrings 0.7 s ✓ ChunkCodecCore 2.1 s ✓ Baselet 0.7 s ✓ Interfaces 0.8 s ✓ Statistics 0.7 s ✓ StaticArraysCore 0.7 s ✓ UniqueVectors 0.6 s ✓ StableRNGs 0.5 s ✓ IfElse 0.5 s ✓ PtrArrays 0.5 s ✓ SimpleBufferStream 0.6 s ✓ ManualMemory 0.6 s ✓ Adapt 0.5 s ✓ DataAPI 0.6 s ✓ SciMLPublic 0.5 s ✓ CommonWorldInvalidations 1.0 s ✓ URIs 3.4 s ✓ UnsafeAtomics 2.3 s ✓ ShowCases 34.8 s ✓ MLStyle 0.6 s ✓ InvertedIndices 0.7 s ✓ InverseFunctions 0.7 s ✓ ThreadSafeDicts 0.6 s ✓ BitFlags 0.5 s ✓ CompositionsBase 0.9 s ✓ AbstractTrees 1.7 s ✓ InitialValues 3.6 s ✓ PrettyPrinting 0.8 s ✓ WorkerUtilities 0.8 s ✓ ComputationalResources 2.4 s ✓ FillArrays 0.5 s ✓ UnPack 0.7 s ✓ Extents 1.2 s ✓ OrderedCollections 1.1 s ✓ FunctionWrappers 0.6 s ✓ HashArrayMappedTries 0.8 s ✓ DocStringExtensions 0.5 s ✓ DefineSingletons 1.4 s ✓ Compiler 0.4 s ✓ SIMDTypes 0.5 s ✓ IteratorInterfaceExtensions 2.0 s ✓ Crayons 0.8 s ✓ ProgressLogging 0.7 s ✓ DelimitedFiles 0.9 s ✓ Requires 1.3 s ✓ ConcurrentUtilities 1.0 s ✓ ZipFile 2.5 s ✓ ProgressMeter 1.2 s ✓ Scratch 2.8 s ✓ SentinelArrays 1.4 s ✓ LoggingExtras 1.8 s ✓ StructUtils 1.7 s ✓ CpuId 2.8 s ✓ PDMats 0.9 s ✓ Compat 1.1 s ✓ ScientificTypesBase 2.0 s ✓ PrecompileTools 2.7 s ✓ LearnAPI 1.6 s ✓ ExceptionUnwrapping 3.3 s ✓ CodeTracking 2.3 s ✓ Rmath_jll 2.3 s ✓ OpenSpecFun_jll 2.3 s ✓ catch22_jll 2.3 s ✓ LLVMOpenMP_jll 2.4 s ✓ MbedTLS_jll 6.0 s ✓ Lazy 2.8 s ✓ SimpleTraits 0.5 s ✓ ConstructionBase → ConstructionBaseLinearAlgebraExt 0.5 s ✓ NameResolution 2.3 s ✓ DataValues 1.0 s ✓ Measurements 0.5 s ✓ IntervalSets → IntervalSetsRandomExt 0.5 s ✓ ConstructionBase → ConstructionBaseIntervalSetsExt 1.9 s ✓ Dictionaries 0.7 s ✓ CodecZlib 0.7 s ✓ ChunkCodecLibZlib 0.9 s ✓ ChunkCodecLibZstd 2.0 s ✓ Statistics → SparseArraysExt 4.2 s ✓ FixedPointNumbers 0.7 s ✓ ScikitLearnBase 1.2 s ✓ Distances 1.4 s ✓ EarlyStopping 0.5 s ✓ IntervalSets → IntervalSetsStatisticsExt 0.7 s ✓ AliasTables 1.9 s ✓ ThreadingUtilities 0.9 s ✓ ArrayInterface 2.0 s ✓ Adapt → AdaptSparseArraysExt 0.9 s ✓ GPUArraysCore 0.7 s ✓ Missings 0.8 s ✓ PooledArrays 0.7 s ✓ Atomix 1.1 s ✓ InverseFunctions → InverseFunctionsDatesExt 1.5 s ✓ InverseFunctions → InverseFunctionsTestExt 4.8 s ✓ OpenSSL 0.5 s ✓ CompositionsBase → CompositionsBaseInverseFunctionsExt 2.5 s ✓ FillArrays → FillArraysSparseArraysExt 0.9 s ✓ FillArrays → FillArraysStatisticsExt 0.8 s ✓ Parameters 0.6 s ✓ ScopedValues 1.3 s ✓ LogExpFunctions 0.4 s ✓ TableTraits 10.0 s ✓ FileIO 1.4 s ✓ RelocatableFolders 1.1 s ✓ StructUtils → StructUtilsStaticArraysCoreExt 2.5 s ✓ FillArrays → FillArraysPDMatsExt 0.5 s ✓ Compat → CompatLinearAlgebraExt 1.1 s ✓ StatisticalTraits 4.4 s ✓ StringManipulation 18.1 s ✓ StaticArrays 4.0 s ✓ RecipesBase 9.9 s ✓ Parsers 17.3 s ✓ Static 12.4 s ✓ JuliaInterpreter 1.5 s ✓ Rmath 2.3 s ✓ XGBoost_jll 5.8 s ✓ XGBoost_GPU_jll 2.5 s ✓ MbedTLS 2.8 s ✓ Setfield 13.1 s ✓ JuliaVariables 1.1 s ✓ StructUtils → StructUtilsMeasurementsExt 2.7 s ✓ ColorTypes 1.8 s ✓ DecisionTree 2.0 s ✓ Distances → DistancesSparseArraysExt 4.5 s ✓ IterationControl 0.5 s ✓ ArrayInterface → ArrayInterfaceStaticArraysCoreExt 2.0 s ✓ ArrayInterface → ArrayInterfaceSparseArraysExt 0.5 s ✓ ArrayInterface → ArrayInterfaceGPUArraysCoreExt 5.8 s ✓ Accessors 0.6 s ✓ LogExpFunctions → LogExpFunctionsInverseFunctionsExt 6.6 s ✓ SpecialFunctions 1.7 s ✓ Tables 1.5 s ✓ TableTraitsUtils 58.6 s ✓ JLD2 2.6 s ✓ ChainRulesCore 2.3 s ✓ FilePathsBase 0.7 s ✓ ContextVariablesX 3.8 s ✓ DataStructures 3.3 s ✓ CategoricalArrays 3.7 s ✓ MLJModelInterface 3.2 s ✓ BitBasis 3.7 s ✓ ArnoldiMethod 1.9 s ✓ StaticArrays → StaticArraysStatisticsExt 2.0 s ✓ ConstructionBase → ConstructionBaseStaticArraysExt 2.1 s ✓ Adapt → AdaptStaticArraysExt 2.4 s ✓ FillArrays → FillArraysStaticArraysExt 1.5 s ✓ IntervalSets → IntervalSetsRecipesBaseExt 1.6 s ✓ Measurements → MeasurementsRecipesBaseExt 8.4 s ✓ JSON 1.2 s ✓ InlineStrings → ParsersExt 1.2 s ✓ BitTwiddlingConvenienceFunctions 3.5 s ✓ CPUSummary 20.2 s ✓ StaticArrayInterface 24.7 s ✓ LoweredCodeUtils 32.5 s ✓ HTTP 3.6 s ✓ SplittablesBase 1.3 s ✓ ColorTypes → StyledStringsExt 2.3 s ✓ Accessors → StaticArraysExt 2.3 s ✓ Accessors → TestExt 2.7 s ✓ Accessors → IntervalSetsExt 2.5 s ✓ Accessors → LinearAlgebraExt 2.6 s ✓ HypergeometricFunctions 1.3 s ✓ Measurements → MeasurementsSpecialFunctionsExt 1.6 s ✓ TableOperations 1.1 s ✓ StructUtils → StructUtilsTablesExt 3.1 s ✓ MLCore 31.9 s ✓ DimensionalData 56.8 s ✓ PrettyTables 1.7 s ✓ IterableTables 6.2 s ✓ JLD2 → UnPackExt 2.1 s ✓ ChainRulesCore → ChainRulesCoreSparseArraysExt 0.6 s ✓ Distances → DistancesChainRulesCoreExt 0.6 s ✓ ArrayInterface → ArrayInterfaceChainRulesCoreExt 3.8 s ✓ LogExpFunctions → LogExpFunctionsChainRulesCoreExt 2.2 s ✓ StaticArrays → StaticArraysChainRulesCoreExt 5.2 s ✓ SpecialFunctions → SpecialFunctionsChainRulesCoreExt 3.2 s ✓ FilePathsBase → FilePathsBaseTestExt 1.2 s ✓ FilePathsBase → FilePathsBaseMmapExt 0.8 s ✓ FLoopsBase 1.5 s ✓ SortingAlgorithms 2.8 s ✓ QuadGK 2.5 s ✓ ARFFFiles 1.4 s ✓ CategoricalArrays → CategoricalArraysRecipesBaseExt 1.3 s ✓ CategoricalArrays → CategoricalArraysSentinelArraysExt 2.7 s ✓ FeatureSelection 2.0 s ✓ MLJWrappers 4.8 s ✓ MLJDecisionTreeInterface 13.0 s ✓ Graphs 11.0 s ✓ KernelAbstractions 2.0 s ✓ TableShowUtils 1.4 s ✓ CategoricalArrays → CategoricalArraysJSONExt 3.9 s ✓ WeakRefStrings 2.0 s ✓ PolyesterWeave 2.3 s ✓ StaticArrayInterface → StaticArrayInterfaceStaticArraysExt 1.4 s ✓ CloseOpenIntervals 1.6 s ✓ LayoutPointers 19.1 s ✓ Revise 6.6 s ✓ FileIO → HTTPExt 1.9 s ✓ BangBang 2.6 s ✓ StatsFuns 2.5 s ✓ DimensionalData → DimensionalDataCategoricalArraysExt 3.6 s ✓ DimensionalData → DimensionalDataSparseArraysExt 2.0 s ✓ DimensionalData → DimensionalDataArrayInterfaceExt 2.0 s ✓ DimensionalData → DimensionalDataChainRulesCoreExt 2.6 s ✓ DimensionalData → DimensionalDataRecipesBaseExt WARNING: Constructor for type "IndexStyle" was extended in `FeatureSets` without explicit qualification or import.  NOTE: Assumed "IndexStyle" refers to `Base.IndexStyle`. This behavior is deprecated and may differ in future versions.  NOTE: This behavior may have differed in Julia versions prior to 1.12.  Hint: If you intended to create a new generic function of the same name, use `function IndexStyle end`.  Hint: To silence the warning, qualify `IndexStyle` as `Base.IndexStyle` in the method signature or explicitly `import Base: IndexStyle`. 7.3 s ✓ TimeseriesFeatures 2.1 s ✓ DimensionalData → DimensionalDataAdaptExt 6.2 s ✓ StatsBase 128.7 s ✓ DataFrames 4.2 s ✓ KernelAbstractions → SparseArraysExt 2.9 s ✓ KernelAbstractions → LinearAlgebraExt 2.9 s ✓ QueryOperators 5.1 s ✓ OpenML 34.3 s ✓ CSV 2.4 s ✓ StrideArraysCore 5.7 s ✓ Revise → DistributedExt 1.5 s ✓ BangBang → BangBangChainRulesCoreExt 1.5 s ✓ BangBang → BangBangTablesExt 2.5 s ✓ BangBang → BangBangStaticArraysExt 2.9 s ✓ MicroCollections 4.6 s ✓ StatsFuns → StatsFunsChainRulesCoreExt 1.3 s ✓ StatsFuns → StatsFunsInverseFunctionsExt 23.1 s ✓ Catch22 3.5 s ✓ LatinHypercubeSampling 2.9 s ✓ PDMats → StatsBaseExt 4.1 s ✓ Discretizers 3.1 s ✓ CategoricalArrays → CategoricalArraysStatsBaseExt 4.4 s ✓ DimensionalData → DimensionalDataStatsBaseExt 4.7 s ✓ TimeseriesFeatures → StatsBaseExt 8.0 s ✓ BangBang → BangBangDataFramesExt 15.6 s ✓ NNlib 2.8 s ✓ Query 2.4 s ✓ Polyester 9.0 s ✓ Transducers 11.6 s ✓ Distributions 5.1 s ✓ SoleBase 3.1 s ✓ NNlib → NNlibSpecialFunctionsExt 4.6 s ✓ SparseMatricesCSR 9.4 s ✓ Transducers → TransducersDataFramesExt 3.2 s ✓ Transducers → TransducersAdaptExt 17.8 s ✓ FLoops 5.7 s ✓ Distributions → DistributionsTestExt 5.1 s ✓ Distributions → DistributionsChainRulesCoreExt 9.2 s ✓ ScientificTypes 36.2 s ✓ SoleLogics 9.0 s ✓ XGBoost 28.9 s ✓ MLUtils 29.8 s ✓ MultiData 11.4 s ✓ CategoricalDistributions 14.8 s ✓ MLJTransforms 10.4 s ✓ MLJXGBoostInterface 27.3 s ✓ StatisticalMeasuresBase 48.9 s ✓ SoleData 23.1 s ✓ MLJModels 60.5 s ✓ StatisticalMeasures 17.9 s ✓ MLJEnsembles 23.9 s ✓ MLJBase WARNING: import of SoleBase.Label into SoleModels conflicts with an existing identifier; ignored. 44.7 s ✓ SoleModels 14.8 s ✓ StatisticalMeasures → ScientificTypesExt 14.9 s ✓ MLJBase → DefaultMeasuresExt 18.5 s ✓ MLJBalancing 20.1 s ✓ MLJIteration 19.0 s ✓ MLJTuning 36.0 s ✓ SoleModels → DecisionTreeExt 35.7 s ✓ SoleModels → XGBoostExt 27.5 s ✓ MLJ 282 dependencies successfully precompiled in 1706 seconds. 45 already precompiled. 2 dependencies had output during precompilation: ┌ TimeseriesFeatures │ WARNING: Constructor for type "IndexStyle" was extended in `FeatureSets` without explicit qualification or import. │ NOTE: Assumed "IndexStyle" refers to `Base.IndexStyle`. This behavior is deprecated and may differ in future versions. │ NOTE: This behavior may have differed in Julia versions prior to 1.12. │ Hint: If you intended to create a new generic function of the same name, use `function IndexStyle end`. │ Hint: To silence the warning, qualify `IndexStyle` as `Base.IndexStyle` in the method signature or explicitly `import Base: IndexStyle`. └ ┌ SoleModels │ WARNING: import of SoleBase.Label into SoleModels conflicts with an existing identifier; ignored. └ Precompilation completed after 1766.38s ################################################################################ # Testing # Testing SoleModels Status `/tmp/jl_qyJLjq/Project.toml` [1520ce14] AbstractTrees v0.4.5 [336ed68f] CSV v0.10.16 [324d7699] CategoricalArrays v1.1.1 [a93c6f00] DataFrames v1.8.2 [7806a523] DecisionTree v0.12.4 [1a297f60] FillArrays v1.16.0 [069b7b12] FunctionWrappers v1.1.3 [c8e1da08] IterTools v1.10.0 [033835bb] JLD2 v0.6.4 [50d2b5c4] Lazy v0.15.1 [add582a8] MLJ v0.23.2 [c6f25543] MLJDecisionTreeInterface v0.4.4 [e80e1ace] MLJModelInterface v1.12.1 [54119dfa] MLJXGBoostInterface v0.3.13 [08abe8d2] PrettyTables v3.3.2 [92933f4c] ProgressMeter v1.11.0 [189a3867] Reexport v1.2.2 [4475fa32] SoleBase v0.13.4 [123f1ae1] SoleData v0.16.8 [b002da8f] SoleLogics v0.13.7 [4249d9c7] SoleModels v0.10.7 [2913bbd2] StatsBase v0.34.11 [4239201d] ThreadSafeDicts v0.1.6 [009559a3] XGBoost v2.5.4 [b77e0a4c] InteractiveUtils v1.11.0 [d6f4376e] Markdown v1.11.0 [9a3f8284] Random v1.11.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_qyJLjq/Manifest.toml` [da404889] ARFFFiles v1.6.0 [1520ce14] AbstractTrees v0.4.5 [7d9f7c33] Accessors v0.1.44 [79e6a3ab] Adapt v4.6.0 [66dad0bd] AliasTables v1.1.3 [dce04be8] ArgCheck v2.5.0 [ec485272] ArnoldiMethod v0.4.0 [4fba245c] ArrayInterface v7.25.0 [a9b6321e] Atomix v1.1.3 [198e06fe] BangBang v0.4.9 [9718e550] Baselet v0.1.1 [50ba71b6] BitBasis v0.9.10 [d1d4a3ce] BitFlags v0.1.10 [62783981] BitTwiddlingConvenienceFunctions v0.1.6 [fa961155] CEnum v0.5.0 [2a0fbf3d] CPUSummary v0.2.7 [336ed68f] CSV v0.10.16 [49dc2e85] Calculus v0.5.2 [acdeb78f] Catch22 v0.7.0 [324d7699] CategoricalArrays v1.1.1 [af321ab8] CategoricalDistributions v0.2.2 [d360d2e6] ChainRulesCore v1.26.1 [0b6fb165] ChunkCodecCore v1.0.1 [4c0bbee4] ChunkCodecLibZlib v1.0.0 [55437552] ChunkCodecLibZstd v1.0.0 [fb6a15b2] CloseOpenIntervals v0.1.13 [da1fd8a2] CodeTracking v3.0.2 [944b1d66] CodecZlib v0.7.8 [3da002f7] ColorTypes v0.12.1 [861a8166] Combinatorics v1.1.0 [f70d9fcc] CommonWorldInvalidations v1.0.0 [34da2185] Compat v4.18.1 [807dbc54] Compiler v0.1.1 [a33af91c] CompositionsBase v0.1.2 [ed09eef8] ComputationalResources v0.3.2 [f0e56b4a] ConcurrentUtilities v2.5.1 [187b0558] ConstructionBase v1.6.0 [6add18c4] ContextVariablesX v0.1.3 [adafc99b] CpuId v0.3.1 [a8cc5b0e] Crayons v4.1.1 [9a962f9c] DataAPI v1.16.0 [a93c6f00] DataFrames v1.8.2 ⌅ [864edb3b] DataStructures v0.18.22 [e2d170a0] DataValueInterfaces v1.0.0 [e7dc6d0d] DataValues v0.4.13 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Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. Testing Running tests... Julia version: 1.14.0-DEV.2291 ################################################## TEST: base.jl TEST: test_tree.jl ################################################## TEST: misc.jl ################################################## TEST: parse.jl ################################################## TEST: juliacon2024.jl [ Info: For silent loading, specify `verbosity=0`. import MLJDecisionTreeInterface ✔ [ Info: Training machine(DecisionTreeClassifier(max_depth = -1, …), …). ▣ ([petal_width] < 0.7) ├✔ setosa └✘ ([petal_width] < 1.65) ├✔ ([petal_length] < 4.95) │ ├✔ versicolor │ └✘ ([petal_width] < 1.55) │ ├✔ virginica │ └✘ ([petal_length] < 5.449999999999999) │ ├✔ versicolor │ └✘ virginica └✘ ([petal_length] < 4.85) ├✔ ([sepal_width] < 3.1) │ ├✔ virginica │ └✘ versicolor └✘ virginica ┌─────────────────────────────────────────────────────────────────────────────── │ ⋯ ├─────────────────────────────────────────────────────────────────────────────── │ ⋯ │ ([petal_widt ⋯ │ ([petal_width] ≥ 0.7) ∧ ([petal_width ⋯ │ ([petal_width] ≥ 0.7) ∧ ([petal_width] < 1.65) ∧ ([petal_length] ≥ 4.95) ∧ ( ⋯ │ ([petal_width] ≥ 0.7) ∧ ([petal_width] < 1.65) ∧ ([petal_length] ≥ 4.95) ∧ ( ⋯ │ ([petal_width] ≥ 0.7) ∧ ([petal_widt ⋯ │ ([petal_width] ≥ 0.7) ∧ ([petal_widt ⋯ │ ([petal_widt ⋯ └─────────────────────────────────────────────────────────────────────────────── 8 columns omitted ┌─────────────────────────────────────────────────────────────────────────────── │ ⋯ ├─────────────────────────────────────────────────────────────────────────────── │ [petal_wid ⋯ │ ([petal_width] ∈ [0.7,1.65)) ∧ ([petal_length ⋯ │ ([petal_width] ∈ [0.7,1.55)) ∧ ([petal_lengt ⋯ │ ([petal_width] ∈ [1.55,1.65)) ∧ ([petal_length] ∈ [4.95,5.4 ⋯ │ ([petal_width] ∈ [1.55,1.65)) ∧ ([petal_length] ∈ [5.44999 ⋯ │ ([petal_width] ∈ [1.65,Inf]) ∧ ([petal_length] ∈ [-Inf,4.85)) ∧ ([sepal_widt ⋯ │ ([petal_width] ∈ [1.65,Inf]) ∧ ([petal_length] ∈ [-Inf,4.85)) ∧ ([sepal_wid ⋯ │ ([petal_width] ∈ [1.65,Inf]) ∧ ([petal_lengt ⋯ └─────────────────────────────────────────────────────────────────────────────── 8 columns omitted ┌─────────────────────────────────────────────────────────────────────────────── │ ⋯ ├─────────────────────────────────────────────────────────────────────────────── │ [petal_wid ⋯ │ ([petal_width] ∈ [0.7,1.65)) ∧ ([petal_length ⋯ │ ([petal_width] ∈ [0.7,1.55)) ∧ ([petal_lengt ⋯ │ ([petal_width] ∈ [1.55,1.65)) ∧ ([petal_length] ∈ [4.95,5.4 ⋯ │ ([petal_width] ∈ [1.55,1.65)) ∧ ([petal_length] ∈ [5.44999 ⋯ │ ([petal_width] ∈ [1.65,Inf]) ∧ ([petal_length] ∈ [-Inf,4.85)) ∧ ([sepal_widt ⋯ │ ([petal_width] ∈ [1.65,Inf]) ∧ ([petal_length] ∈ [-Inf,4.85)) ∧ ([sepal_wid ⋯ │ ([petal_width] ∈ [1.65,Inf]) ∧ ([petal_lengt ⋯ └─────────────────────────────────────────────────────────────────────────────── 9 columns omitted ┌─────────────────────────────────────────────────────────────────────────────── │ ⋯ ├─────────────────────────────────────────────────────────────────────────────── │ ⋯ │ [petal ⋯ │ (([petal_width] ∈ [0.7,1.55)) ∧ ([petal_length] ∈ [4.95,Inf])) ∨ (([petal_wi ⋯ └─────────────────────────────────────────────────────────────────────────────── 8 columns omitted ################################################## TEST: linear-form-utilities.jl ################################################## TEST: /home/pkgeval/.julia/packages/SoleModels/iRRCx/pluto-demo.jl Progress: 25%|██████████▎ | ETA: 0:00:26 Progress: 62%|█████████████████████████▋ | ETA: 0:00:08 Progress: 75%|██████████████████████████████▊ | ETA: 0:00:04 Progress: 88%|███████████████████████████████████▉ | ETA: 0:00:02 Progress: 100%|█████████████████████████████████████████| Time: 0:00:14 ################################################## TEST: DecisionTreeExt/tree.jl Training set size: (120, 4) - (120,) Test set size: (30, 4) - (30,) Training set type: DataFrame - CategoricalArrays.CategoricalVector{String, UInt32, String, CategoricalArrays.CategoricalValue{String, UInt32}, Union{}} Test set type: DataFrame - CategoricalArrays.CategoricalVector{String, UInt32, String, CategoricalArrays.CategoricalValue{String, UInt32}, Union{}} [ Info: For silent loading, specify `verbosity=0`. import MLJDecisionTreeInterface ✔ [ Info: Training machine(DecisionTreeClassifier(max_depth = -1, …), …). ▣ ([petal_length] < 2.45) ├✔ setosa : (ninstances = 41, ncovered = 41, confidence = 1.0, lift = 1.0) └✘ ([petal_width] < 1.75) ├✔ ([petal_length] < 4.95) │ ├✔ ([petal_width] < 1.65) │ │ ├✔ versicolor : (ninstances = 37, ncovered = 37, confidence = 1.0, lift = 1.0) │ │ └✘ virginica : (ninstances = 1, ncovered = 1, confidence = 1.0, lift = 1.0) │ └✘ ([petal_width] < 1.55) │ ├✔ virginica : (ninstances = 2, ncovered = 2, confidence = 1.0, lift = 1.0) │ └✘ ([petal_length] < 5.449999999999999) │ ├✔ versicolor : (ninstances = 2, ncovered = 2, confidence = 1.0, lift = 1.0) │ └✘ virginica : (ninstances = 1, ncovered = 1, confidence = 1.0, lift = 1.0) └✘ virginica : (ninstances = 36, ncovered = 36, confidence = 1.0, lift = 1.0) ▣ ([petal_length] < 2.45) ↣ setosa : (ninstances = 120, ncovered = 41, coverage = 0.34, confidence = 1.0, lift = 2.93, natoms = 1) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] < 4.95)) ∧ (([petal_width] < 1.65)) ↣ versicolor : (ninstances = 120, ncovered = 37, coverage = 0.31, confidence = 1.0, lift = 3.08, natoms = 4) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] < 4.95)) ∧ (([petal_width] ≥ 1.65)) ↣ virginica : (ninstances = 120, ncovered = 1, coverage = 0.01, confidence = 1.0, lift = 3.0, natoms = 4) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] ≥ 4.95)) ∧ (([petal_width] < 1.55)) ↣ virginica : (ninstances = 120, ncovered = 2, coverage = 0.02, confidence = 1.0, lift = 3.0, natoms = 4) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] ≥ 4.95)) ∧ (([petal_width] ≥ 1.55)) ∧ (([petal_length] < 5.449999999999999)) ↣ versicolor : (ninstances = 120, ncovered = 2, coverage = 0.02, confidence = 1.0, lift = 3.08, natoms = 5) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] ≥ 4.95)) ∧ (([petal_width] ≥ 1.55)) ∧ (([petal_length] ≥ 5.449999999999999)) ↣ virginica : (ninstances = 120, ncovered = 1, coverage = 0.01, confidence = 1.0, lift = 3.0, natoms = 5) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] ≥ 1.75)) ↣ virginica : (ninstances = 120, ncovered = 36, coverage = 0.3, confidence = 1.0, lift = 3.0, natoms = 2) ▣ ([petal_length] < 2.45) ↣ setosa : (ninstances = 41, ncovered = 41, confidence = 1.0, lift = 1.0) : (ninstances = 120, ncovered = 41, coverage = 0.34, confidence = 1.0, lift = 2.93, natoms = 1) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] < 4.95)) ∧ (([petal_width] < 1.65)) ↣ versicolor : (ninstances = 37, ncovered = 37, confidence = 1.0, lift = 1.0) : (ninstances = 120, ncovered = 37, coverage = 0.31, confidence = 1.0, lift = 3.08, natoms = 4) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] < 4.95)) ∧ (([petal_width] ≥ 1.65)) ↣ virginica : (ninstances = 1, ncovered = 1, confidence = 1.0, lift = 1.0) : (ninstances = 120, ncovered = 1, coverage = 0.01, confidence = 1.0, lift = 3.0, natoms = 4) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] ≥ 4.95)) ∧ (([petal_width] < 1.55)) ↣ virginica : (ninstances = 2, ncovered = 2, confidence = 1.0, lift = 1.0) : (ninstances = 120, ncovered = 2, coverage = 0.02, confidence = 1.0, lift = 3.0, natoms = 4) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] ≥ 4.95)) ∧ (([petal_width] ≥ 1.55)) ∧ (([petal_length] < 5.449999999999999)) ↣ versicolor : (ninstances = 2, ncovered = 2, confidence = 1.0, lift = 1.0) : (ninstances = 120, ncovered = 2, coverage = 0.02, confidence = 1.0, lift = 3.08, natoms = 5) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] ≥ 4.95)) ∧ (([petal_width] ≥ 1.55)) ∧ (([petal_length] ≥ 5.449999999999999)) ↣ virginica : (ninstances = 1, ncovered = 1, confidence = 1.0, lift = 1.0) : (ninstances = 120, ncovered = 1, coverage = 0.01, confidence = 1.0, lift = 3.0, natoms = 5) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] ≥ 1.75)) ↣ virginica : (ninstances = 36, ncovered = 36, confidence = 1.0, lift = 1.0) : (ninstances = 120, ncovered = 36, coverage = 0.3, confidence = 1.0, lift = 3.0, natoms = 2) ▣ ([petal_length] < 2.45) : (ninstances = 120, ncovered = 41, coverage = 0.34, confidence = 1.0, lift = 2.93, natoms = 1) └✔ setosa : (ninstances = 41, ncovered = 41, confidence = 1.0, lift = 1.0) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] < 4.95)) ∧ (([petal_width] < 1.65)) : (ninstances = 120, ncovered = 37, coverage = 0.31, confidence = 1.0, lift = 3.08, natoms = 4) └✔ versicolor : (ninstances = 37, ncovered = 37, confidence = 1.0, lift = 1.0) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] < 4.95)) ∧ (([petal_width] ≥ 1.65)) : (ninstances = 120, ncovered = 1, coverage = 0.01, confidence = 1.0, lift = 3.0, natoms = 4) └✔ virginica : (ninstances = 1, ncovered = 1, confidence = 1.0, lift = 1.0) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] ≥ 4.95)) ∧ (([petal_width] < 1.55)) : (ninstances = 120, ncovered = 2, coverage = 0.02, confidence = 1.0, lift = 3.0, natoms = 4) └✔ virginica : (ninstances = 2, ncovered = 2, confidence = 1.0, lift = 1.0) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] ≥ 4.95)) ∧ (([petal_width] ≥ 1.55)) ∧ (([petal_length] < 5.449999999999999)) : (ninstances = 120, ncovered = 2, coverage = 0.02, confidence = 1.0, lift = 3.08, natoms = 5) └✔ versicolor : (ninstances = 2, ncovered = 2, confidence = 1.0, lift = 1.0) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] ≥ 4.95)) ∧ (([petal_width] ≥ 1.55)) ∧ (([petal_length] ≥ 5.449999999999999)) : (ninstances = 120, ncovered = 1, coverage = 0.01, confidence = 1.0, lift = 3.0, natoms = 5) └✔ virginica : (ninstances = 1, ncovered = 1, confidence = 1.0, lift = 1.0) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] ≥ 1.75)) : (ninstances = 120, ncovered = 36, coverage = 0.3, confidence = 1.0, lift = 3.0, natoms = 2) └✔ virginica : (ninstances = 36, ncovered = 36, confidence = 1.0, lift = 1.0) ▣ ([petal_length] < 2.45) ↣ setosa : (ninstances = 120, ncovered = 41, coverage = 0.34, confidence = 1.0, lift = 2.93, natoms = 1) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] < 4.95)) ∧ (([petal_width] < 1.65)) ↣ versicolor : (ninstances = 120, ncovered = 37, coverage = 0.31, confidence = 1.0, lift = 3.08, natoms = 4) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] < 4.95)) ∧ (([petal_width] ≥ 1.65)) ↣ virginica : (ninstances = 120, ncovered = 1, coverage = 0.01, confidence = 1.0, lift = 3.0, natoms = 4) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] ≥ 4.95)) ∧ (([petal_width] < 1.55)) ↣ virginica : (ninstances = 120, ncovered = 2, coverage = 0.02, confidence = 1.0, lift = 3.0, natoms = 4) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] ≥ 4.95)) ∧ (([petal_width] ≥ 1.55)) ∧ (([petal_length] < 5.449999999999999)) ↣ versicolor : (ninstances = 120, ncovered = 2, coverage = 0.02, confidence = 1.0, lift = 3.08, natoms = 5) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] ≥ 4.95)) ∧ (([petal_width] ≥ 1.55)) ∧ (([petal_length] ≥ 5.449999999999999)) ↣ virginica : (ninstances = 120, ncovered = 1, coverage = 0.01, confidence = 1.0, lift = 3.0, natoms = 5) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] ≥ 1.75)) ↣ virginica : (ninstances = 120, ncovered = 36, coverage = 0.3, confidence = 1.0, lift = 3.0, natoms = 2) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] < 4.95)) ∧ (([petal_width] ≥ 1.65)) ↣ virginica : (ninstances = 120, ncovered = 1, coverage = 0.008333333333333333, confidence = 1.0, lift = 3.0, natoms = 4, length = 4) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] ≥ 4.95)) ∧ (([petal_width] ≥ 1.55)) ∧ (([petal_length] ≥ 5.449999999999999)) ↣ virginica : (ninstances = 120, ncovered = 1, coverage = 0.008333333333333333, confidence = 1.0, lift = 3.0, natoms = 5, length = 5) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] ≥ 4.95)) ∧ (([petal_width] < 1.55)) ↣ virginica : (ninstances = 120, ncovered = 2, coverage = 0.016666666666666666, confidence = 1.0, lift = 3.0, natoms = 4, length = 4) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] ≥ 4.95)) ∧ (([petal_width] ≥ 1.55)) ∧ (([petal_length] < 5.449999999999999)) ↣ versicolor : (ninstances = 120, ncovered = 2, coverage = 0.016666666666666666, confidence = 1.0, lift = 3.0769230769230766, natoms = 5, length = 5) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] ≥ 1.75)) ↣ virginica : (ninstances = 120, ncovered = 36, coverage = 0.3, confidence = 1.0, lift = 3.0, natoms = 2, length = 2) ▣ (([petal_length] ≥ 2.45)) ∧ (([petal_width] < 1.75)) ∧ (([petal_length] < 4.95)) ∧ (([petal_width] < 1.65)) ↣ versicolor : (ninstances = 120, ncovered = 37, coverage = 0.30833333333333335, confidence = 1.0, lift = 3.0769230769230766, natoms = 4, length = 4) ▣ ([petal_length] < 2.45) ↣ setosa : (ninstances = 120, ncovered = 41, coverage = 0.3416666666666667, confidence = 1.0, lift = 2.926829268292683, natoms = 1, length = 1) [ Info: For silent loading, specify `verbosity=0`. import MLJDecisionTreeInterface ✔ TEST: DecisionTreeExt/forest.jl Training set size: (120, 4) - (120,) Test set size: (30, 4) - (30,) Training set type: DataFrame - CategoricalArrays.CategoricalVector{String, UInt32, String, CategoricalArrays.CategoricalValue{String, UInt32}, Union{}} Test set type: DataFrame - CategoricalArrays.CategoricalVector{String, UInt32, String, CategoricalArrays.CategoricalValue{String, UInt32}, Union{}} [ Info: For silent loading, specify `verbosity=0`. import MLJDecisionTreeInterface ✔ [ Info: Training machine(RandomForestClassifier(max_depth = 3, …), …). ▣ Ensemble{UInt32} of 10 models of type Branch{CategoricalArrays.CategoricalValue{String, UInt32}} ├[1/10]┐ ([petal_length] < 2.35) │ ├✔ setosa : (ninstances = 9, ncovered = 9, confidence = 1.0, lift = 1.0) │ └✘ ([petal_width] < 1.75) │ ├✔ ([petal_width] < 1.35) │ │ ├✔ versicolor : (ninstances = 6, ncovered = 6, confidence = 1.0, lift = 1.0) │ │ └✘ versicolor : (ninstances = 5, ncovered = 5, confidence = 0.8, lift = 1.0) │ └✘ virginica : (ninstances = 10, ncovered = 10, confidence = 0.9, lift = 1.0) ├[2/10]┐ ([sepal_length] < 5.75) │ ├✔ ([petal_length] < 2.45) │ │ ├✔ setosa : (ninstances = 9, ncovered = 9, confidence = 1.0, lift = 1.0) │ │ └✘ versicolor : (ninstances = 5, ncovered = 5, confidence = 0.8, lift = 1.0) │ └✘ ([petal_width] < 1.65) │ ├✔ ([petal_length] < 2.6) │ │ ├✔ setosa : (ninstances = 0, ncovered = 0, confidence = NaN, lift = NaN) │ │ └✘ versicolor : (ninstances = 7, ncovered = 7, confidence = 0.86, lift = 1.0) │ └✘ virginica : (ninstances = 9, ncovered = 9, confidence = 0.89, lift = 1.0) ├[3/10]┐ ([petal_width] < 0.7) │ ├✔ setosa : (ninstances = 9, ncovered = 9, confidence = 1.0, lift = 1.0) │ └✘ ([petal_width] < 1.75) │ ├✔ ([petal_length] < 4.85) │ │ ├✔ versicolor : (ninstances = 10, ncovered = 10, confidence = 1.0, lift = 1.0) │ │ └✘ virginica : (ninstances = 1, ncovered = 1, confidence = 1.0, lift = 1.0) │ └✘ virginica : (ninstances = 10, ncovered = 10, confidence = 0.9, lift = 1.0) ├[4/10]┐ ([petal_width] < 0.7) │ ├✔ setosa : (ninstances = 9, ncovered = 9, confidence = 1.0, lift = 1.0) │ └✘ ([petal_length] < 4.95) │ ├✔ versicolor : (ninstances = 13, ncovered = 13, confidence = 0.85, lift = 1.0) │ └✘ virginica : (ninstances = 8, ncovered = 8, confidence = 1.0, lift = 1.0) ├[5/10]┐ ([petal_width] < 0.75) │ ├✔ setosa : (ninstances = 9, ncovered = 9, confidence = 1.0, lift = 1.0) │ └✘ ([petal_length] < 5.05) │ ├✔ ([sepal_length] < 6.25) │ │ ├✔ versicolor : (ninstances = 12, ncovered = 12, confidence = 0.92, lift = 1.0) │ │ └✘ versicolor : (ninstances = 1, ncovered = 1, confidence = 0.0, lift = NaN) │ └✘ virginica : (ninstances = 8, ncovered = 8, confidence = 1.0, lift = 1.0) ├[6/10]┐ ([sepal_length] < 5.75) │ ├✔ ([petal_length] < 2.45) │ │ ├✔ setosa : (ninstances = 9, ncovered = 9, confidence = 1.0, lift = 1.0) │ │ └✘ ([sepal_length] < 4.95) │ │ ├✔ virginica : (ninstances = 0, ncovered = 0, confidence = NaN, lift = NaN) │ │ └✘ versicolor : (ninstances = 5, ncovered = 5, confidence = 0.8, lift = 1.0) │ └✘ ([petal_width] < 1.7000000000000002) │ ├✔ ([petal_length] < 4.95) │ │ ├✔ versicolor : (ninstances = 6, ncovered = 6, confidence = 1.0, lift = 1.0) │ │ └✘ virginica : (ninstances = 1, ncovered = 1, confidence = 1.0, lift = 1.0) │ └✘ virginica : (ninstances = 9, ncovered = 9, confidence = 0.89, lift = 1.0) ├[7/10]┐ ([petal_length] < 2.45) │ ├✔ setosa : (ninstances = 9, ncovered = 9, confidence = 1.0, lift = 1.0) │ └✘ ([petal_width] < 1.75) │ ├✔ ([sepal_length] < 7.1) │ │ ├✔ versicolor : (ninstances = 11, ncovered = 11, confidence = 0.91, lift = 1.0) │ │ └✘ virginica : (ninstances = 0, ncovered = 0, confidence = NaN, lift = NaN) │ └✘ virginica : (ninstances = 10, ncovered = 10, confidence = 0.9, lift = 1.0) ├[8/10]┐ ([petal_width] < 0.75) │ ├✔ setosa : (ninstances = 9, ncovered = 9, confidence = 1.0, lift = 1.0) │ └✘ ([petal_width] < 1.65) │ ├✔ ([petal_length] < 4.9) │ │ ├✔ versicolor : (ninstances = 10, ncovered = 10, confidence = 1.0, lift = 1.0) │ │ └✘ virginica : (ninstances = 1, ncovered = 1, confidence = 1.0, lift = 1.0) │ └✘ virginica : (ninstances = 10, ncovered = 10, confidence = 0.9, lift = 1.0) ├[9/10]┐ ([sepal_length] < 5.9) │ ├✔ ([petal_length] < 2.35) │ │ ├✔ setosa : (ninstances = 9, ncovered = 9, confidence = 1.0, lift = 1.0) │ │ └✘ versicolor : (ninstances = 6, ncovered = 6, confidence = 0.83, lift = 1.0) │ └✘ ([petal_width] < 1.55) │ ├✔ ([sepal_length] < 6.1) │ │ ├✔ virginica : (ninstances = 2, ncovered = 2, confidence = 0.0, lift = NaN) │ │ └✘ versicolor : (ninstances = 4, ncovered = 4, confidence = 0.75, lift = 1.0) │ └✘ virginica : (ninstances = 9, ncovered = 9, confidence = 0.89, lift = 1.0) └[10/10]┐ ([petal_width] < 0.75) ├✔ setosa : (ninstances = 9, ncovered = 9, confidence = 1.0, lift = 1.0) └✘ ([sepal_length] < 5.75) ├✔ ([petal_width] < 1.6) │ ├✔ versicolor : (ninstances = 4, ncovered = 4, confidence = 1.0, lift = 1.0) │ └✘ virginica : (ninstances = 1, ncovered = 1, confidence = 1.0, lift = 1.0) └✘ ([sepal_length] < 7.050000000000001) ├✔ virginica : (ninstances = 14, ncovered = 14, confidence = 0.5, lift = 1.0) └✘ virginica : (ninstances = 2, ncovered = 2, confidence = 1.0, lift = 1.0) [ Info: For silent loading, specify `verbosity=0`. import MLJDecisionTreeInterface ✔ TEST: DecisionTreeExt/adaboost.jl Training set size: (105, 4) - (105,) Test set size: (45, 4) - (45,) Training set type: DataFrame - CategoricalArrays.CategoricalVector{String, UInt32, String, CategoricalArrays.CategoricalValue{String, UInt32}, Union{}} Test set type: DataFrame - CategoricalArrays.CategoricalVector{String, UInt32, String, CategoricalArrays.CategoricalValue{String, UInt32}, Union{}} [ Info: For silent loading, specify `verbosity=0`. import MLJDecisionTreeInterface ✔ ▣ Ensemble{UInt32} of 10 models of type Branch{CategoricalArrays.CategoricalValue{String, UInt32}} ├[1/10]┐ ([petal_width] < 0.8) │ ├✔ setosa : (ninstances = 17, ncovered = 17, confidence = 1.0, lift = 1.0) │ └✘ versicolor : (ninstances = 28, ncovered = 28, confidence = 0.46, lift = 1.0) ├[2/10]┐ ([petal_length] < 2.45) │ ├✔ setosa : (ninstances = 17, ncovered = 17, confidence = 1.0, lift = 1.0) │ └✘ virginica : (ninstances = 28, ncovered = 28, confidence = 0.54, lift = 1.0) ├[3/10]┐ ([petal_width] < 1.75) │ ├✔ versicolor : (ninstances = 32, ncovered = 32, confidence = 0.41, lift = 1.0) │ └✘ virginica : (ninstances = 13, ncovered = 13, confidence = 1.0, lift = 1.0) ├[4/10]┐ ([petal_width] < 0.8) │ ├✔ setosa : (ninstances = 17, ncovered = 17, confidence = 1.0, lift = 1.0) │ └✘ versicolor : (ninstances = 28, ncovered = 28, confidence = 0.46, lift = 1.0) ├[5/10]┐ ([petal_length] < 2.45) │ ├✔ setosa : (ninstances = 17, ncovered = 17, confidence = 1.0, lift = 1.0) │ └✘ virginica : (ninstances = 28, ncovered = 28, confidence = 0.54, lift = 1.0) ├[6/10]┐ ([petal_length] < 4.85) │ ├✔ versicolor : (ninstances = 29, ncovered = 29, confidence = 0.38, lift = 1.0) │ └✘ virginica : (ninstances = 16, ncovered = 16, confidence = 0.88, lift = 1.0) ├[7/10]┐ ([petal_length] < 2.45) │ ├✔ setosa : (ninstances = 17, ncovered = 17, confidence = 1.0, lift = 1.0) │ └✘ versicolor : (ninstances = 28, ncovered = 28, confidence = 0.46, lift = 1.0) ├[8/10]┐ ([petal_width] < 0.8) │ ├✔ setosa : (ninstances = 17, ncovered = 17, confidence = 1.0, lift = 1.0) │ └✘ virginica : (ninstances = 28, ncovered = 28, confidence = 0.54, lift = 1.0) ├[9/10]┐ ([sepal_length] < 4.95) │ ├✔ virginica : (ninstances = 9, ncovered = 9, confidence = 0.0, lift = NaN) │ └✘ versicolor : (ninstances = 36, ncovered = 36, confidence = 0.36, lift = 1.0) └[10/10]┐ ([petal_length] < 2.45) ├✔ setosa : (ninstances = 17, ncovered = 17, confidence = 1.0, lift = 1.0) └✘ virginica : (ninstances = 28, ncovered = 28, confidence = 0.54, lift = 1.0) [ Info: For silent loading, specify `verbosity=0`. import MLJDecisionTreeInterface ✔ [ Info: For silent loading, specify `verbosity=0`. import MLJDecisionTreeInterface ✔ AdaBoost accuracy: 0.9555555555555556 DecisionTree accuracy: 0.8888888888888888 RandomForest accuracy: 0.9555555555555556 [ Info: For silent loading, specify `verbosity=0`. import MLJDecisionTreeInterface ✔ ################################################## TEST: XGBoostExt/xgboost_classifier.jl Training set size: (105, 4) - (105,) Test set size: (45, 4) - (45,) Training set type: DataFrame - CategoricalArrays.CategoricalVector{String, UInt32, String, CategoricalArrays.CategoricalValue{String, UInt32}, Union{}} Test set type: DataFrame - CategoricalArrays.CategoricalVector{String, UInt32, String, CategoricalArrays.CategoricalValue{String, UInt32}, Union{}} [ Info: For silent loading, specify `verbosity=0`. import MLJXGBoostInterface ✔ [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74042857487996416 [ Info: [2] train-mlogloss:0.52959098986216957 [ Info: [3] train-mlogloss:0.39248797978673661 [ Info: [4] train-mlogloss:0.29784015984762280 [ Info: [5] train-mlogloss:0.23065083679698761 [ Info: [6] train-mlogloss:0.17993504050232115 [ Info: [7] train-mlogloss:0.14291282310372308 [ Info: [8] train-mlogloss:0.11707862722022193 [ Info: [9] train-mlogloss:0.09605735504911059 [ Info: [10] train-mlogloss:0.08039097104753767 [ Info: Training rounds complete. [ Info: For silent loading, specify `verbosity=0`. import MLJDecisionTreeInterface ✔ [ Info: For silent loading, specify `verbosity=0`. import MLJDecisionTreeInterface ✔ XGBoost accuracy: 0.9333333333333333 DecisionTree accuracy: 0.9555555555555556 RandomForest accuracy: 0.9333333333333333 XGBoostExt: Test Failed at /home/pkgeval/.julia/packages/SoleModels/iRRCx/test/XGBoostExt/xgboost_classifier.jl:125 Expression: xg_accuracy ≥ rm_accuracy ≥ dt_accuracy Evaluated: 0.9333333333333333 ≥ 0.9333333333333333 ≥ 0.9555555555555556 Stacktrace: [1] top-level scope @ ~/.julia/packages/SoleModels/iRRCx/test/XGBoostExt/xgboost_classifier.jl:560 [2] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined] [3] include(mapexpr::Function, mod::Module, _path::String) @ Base Base.jl:327 [4] run_tests(list::Vector{String}) @ Main ~/.julia/packages/SoleModels/iRRCx/test/runtests.jl:8 [5] macro expansion @ ~/.julia/packages/SoleModels/iRRCx/test/runtests.jl:36 [inlined] [6] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [7] macro expansion @ ~/.julia/packages/SoleModels/iRRCx/test/runtests.jl:36 [inlined] [8] macro expansion @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined] [9] top-level scope @ ~/.julia/packages/SoleModels/iRRCx/test/runtests.jl:31 [ Info: For silent loading, specify `verbosity=0`. import MLJXGBoostInterface ✔ [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97108645439147945 [ Info: [2] train-mlogloss:0.86377177749361311 [ Info: [3] train-mlogloss:0.77233211710339500 [ Info: [4] train-mlogloss:0.69221566347848806 [ Info: [5] train-mlogloss:0.62278509253547309 [ Info: [6] train-mlogloss:0.56222322554815385 [ Info: [7] train-mlogloss:0.50911712305886403 [ Info: [8] train-mlogloss:0.46234442421368188 [ Info: [9] train-mlogloss:0.42099781604040237 [ Info: [10] train-mlogloss:0.38433285469100587 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85337008010773430 [ Info: [2] train-mlogloss:0.68041899261020478 [ Info: [3] train-mlogloss:0.55019682078134446 [ Info: [4] train-mlogloss:0.45119516111555552 [ Info: [5] train-mlogloss:0.37442616706802734 [ Info: [6] train-mlogloss:0.31406550748007639 [ Info: [7] train-mlogloss:0.26611783107121784 [ Info: [8] train-mlogloss:0.22773031663326990 [ Info: [9] train-mlogloss:0.19680509510494415 [ Info: [10] train-mlogloss:0.17176406724112375 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74583915472030637 [ Info: [2] train-mlogloss:0.53470991055170691 [ Info: [3] train-mlogloss:0.39748490197317943 [ Info: [4] train-mlogloss:0.30370020781244550 [ Info: [5] train-mlogloss:0.23771505739007678 [ Info: [6] train-mlogloss:0.19040401790823255 [ Info: [7] train-mlogloss:0.15256902171032768 [ Info: [8] train-mlogloss:0.12456002703734807 [ Info: [9] train-mlogloss:0.10210393560784203 [ Info: [10] train-mlogloss:0.08494759116853987 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97108645439147945 [ Info: [2] train-mlogloss:0.86377177749361311 [ Info: [3] train-mlogloss:0.77233211710339500 [ Info: [4] train-mlogloss:0.69221566347848806 [ Info: [5] train-mlogloss:0.62278509253547309 [ Info: [6] train-mlogloss:0.56222322554815385 [ Info: [7] train-mlogloss:0.50911712305886403 [ Info: [8] train-mlogloss:0.46234442421368188 [ Info: [9] train-mlogloss:0.42099781604040237 [ Info: [10] train-mlogloss:0.38433285469100587 [ Info: [11] train-mlogloss:0.35173162307058065 [ Info: [12] train-mlogloss:0.32267563541730243 [ Info: [13] train-mlogloss:0.29672600002515881 [ Info: [14] train-mlogloss:0.27350856008983793 [ Info: [15] train-mlogloss:0.25270199818270545 [ Info: [16] train-mlogloss:0.23402889158044543 [ Info: [17] train-mlogloss:0.21724845497381121 [ Info: [18] train-mlogloss:0.20215076534521012 [ Info: [19] train-mlogloss:0.18855218220324743 [ Info: [20] train-mlogloss:0.17517407635847729 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85337008010773430 [ Info: [2] train-mlogloss:0.68041899261020478 [ Info: [3] train-mlogloss:0.55019682078134446 [ Info: [4] train-mlogloss:0.45119516111555552 [ Info: [5] train-mlogloss:0.37442616706802734 [ Info: [6] train-mlogloss:0.31406550748007639 [ Info: [7] train-mlogloss:0.26611783107121784 [ Info: [8] train-mlogloss:0.22773031663326990 [ Info: [9] train-mlogloss:0.19680509510494415 [ Info: [10] train-mlogloss:0.17176406724112375 [ Info: [11] train-mlogloss:0.14934622340259099 [ Info: [12] train-mlogloss:0.13083845845290593 [ Info: [13] train-mlogloss:0.11448201771293368 [ Info: [14] train-mlogloss:0.10078195212852387 [ Info: [15] train-mlogloss:0.08930896038100833 [ Info: [16] train-mlogloss:0.08072252514816466 [ Info: [17] train-mlogloss:0.07268897692362468 [ Info: [18] train-mlogloss:0.06647622947181975 [ Info: [19] train-mlogloss:0.05989613313050497 [ Info: [20] train-mlogloss:0.05475671770317214 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74583915472030637 [ Info: [2] train-mlogloss:0.53470991055170691 [ Info: [3] train-mlogloss:0.39748490197317943 [ Info: [4] train-mlogloss:0.30370020781244550 [ Info: [5] train-mlogloss:0.23771505739007678 [ Info: [6] train-mlogloss:0.19040401790823255 [ Info: [7] train-mlogloss:0.15256902171032768 [ Info: [8] train-mlogloss:0.12456002703734807 [ Info: [9] train-mlogloss:0.10210393560784203 [ Info: [10] train-mlogloss:0.08494759116853987 [ Info: [11] train-mlogloss:0.07312472682623636 [ Info: [12] train-mlogloss:0.06289548001119069 [ Info: [13] train-mlogloss:0.05554904382498491 [ Info: [14] train-mlogloss:0.04830665483715988 [ Info: [15] train-mlogloss:0.04413454559232508 [ Info: [16] train-mlogloss:0.04005234288495212 [ Info: [17] train-mlogloss:0.03683335091918707 [ Info: [18] train-mlogloss:0.03449804257778894 [ Info: [19] train-mlogloss:0.03240978849076089 [ Info: [20] train-mlogloss:0.03096451766434170 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96882668960662111 [ Info: [2] train-mlogloss:0.85985381716773623 [ Info: [3] train-mlogloss:0.76734603643417354 [ Info: [4] train-mlogloss:0.68778227908270695 [ Info: [5] train-mlogloss:0.61838555108933224 [ Info: [6] train-mlogloss:0.55778954539980208 [ Info: [7] train-mlogloss:0.50460373191606434 [ Info: [8] train-mlogloss:0.45771457183928715 [ Info: [9] train-mlogloss:0.41656059253783451 [ Info: [10] train-mlogloss:0.37997880663190570 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84909702993574598 [ Info: [2] train-mlogloss:0.67440279154550464 [ Info: [3] train-mlogloss:0.54450918606349397 [ Info: [4] train-mlogloss:0.44552257259686789 [ Info: [5] train-mlogloss:0.36919304870423819 [ Info: [6] train-mlogloss:0.30889779925346372 [ Info: [7] train-mlogloss:0.26120953616641818 [ Info: [8] train-mlogloss:0.22205992028826760 [ Info: [9] train-mlogloss:0.19006149059250241 [ Info: [10] train-mlogloss:0.16368774856839860 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73981271187464392 [ Info: [2] train-mlogloss:0.52927702665328979 [ Info: [3] train-mlogloss:0.39367959953489756 [ Info: [4] train-mlogloss:0.30030087743486678 [ Info: [5] train-mlogloss:0.23423779195263272 [ Info: [6] train-mlogloss:0.18500665227572125 [ Info: [7] train-mlogloss:0.14831622356460208 [ Info: [8] train-mlogloss:0.12024731650238946 [ Info: [9] train-mlogloss:0.09958935798633667 [ Info: [10] train-mlogloss:0.08358181878214790 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96882668960662111 [ Info: [2] train-mlogloss:0.85985381716773623 [ Info: [3] train-mlogloss:0.76734603643417354 [ Info: [4] train-mlogloss:0.68778227908270695 [ Info: [5] train-mlogloss:0.61838555108933224 [ Info: [6] train-mlogloss:0.55778954539980208 [ Info: [7] train-mlogloss:0.50460373191606434 [ Info: [8] train-mlogloss:0.45771457183928715 [ Info: [9] train-mlogloss:0.41656059253783451 [ Info: [10] train-mlogloss:0.37997880663190570 [ Info: [11] train-mlogloss:0.34738119272958667 [ Info: [12] train-mlogloss:0.31825356795674281 [ Info: [13] train-mlogloss:0.29238381641251698 [ Info: [14] train-mlogloss:0.26919005073252178 [ Info: [15] train-mlogloss:0.24836455455848150 [ Info: [16] train-mlogloss:0.22917527769293103 [ Info: [17] train-mlogloss:0.21191179028579166 [ Info: [18] train-mlogloss:0.19624096651872000 [ Info: [19] train-mlogloss:0.18206248297577812 [ Info: [20] train-mlogloss:0.16910996877011800 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84909702993574598 [ Info: [2] train-mlogloss:0.67440279154550464 [ Info: [3] train-mlogloss:0.54450918606349397 [ Info: [4] train-mlogloss:0.44552257259686789 [ Info: [5] train-mlogloss:0.36919304870423819 [ Info: [6] train-mlogloss:0.30889779925346372 [ Info: [7] train-mlogloss:0.26120953616641818 [ Info: [8] train-mlogloss:0.22205992028826760 [ Info: [9] train-mlogloss:0.19006149059250241 [ Info: [10] train-mlogloss:0.16368774856839860 [ Info: [11] train-mlogloss:0.14190081726937068 [ Info: [12] train-mlogloss:0.12366871053264254 [ Info: [13] train-mlogloss:0.10837456385294596 [ Info: [14] train-mlogloss:0.09621905038754146 [ Info: [15] train-mlogloss:0.08579394490945907 [ Info: [16] train-mlogloss:0.07694795500664484 [ Info: [17] train-mlogloss:0.06952216178178787 [ Info: [18] train-mlogloss:0.06320734442699523 [ Info: [19] train-mlogloss:0.05796017966100148 [ Info: [20] train-mlogloss:0.05326318964362144 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73981271187464392 [ Info: [2] train-mlogloss:0.52927702665328979 [ Info: [3] train-mlogloss:0.39367959953489756 [ Info: [4] train-mlogloss:0.30030087743486678 [ Info: [5] train-mlogloss:0.23423779195263272 [ Info: [6] train-mlogloss:0.18500665227572125 [ Info: [7] train-mlogloss:0.14831622356460208 [ Info: [8] train-mlogloss:0.12024731650238946 [ Info: [9] train-mlogloss:0.09958935798633667 [ Info: [10] train-mlogloss:0.08358181878214790 [ Info: [11] train-mlogloss:0.07135912516996974 [ Info: [12] train-mlogloss:0.06185790640967233 [ Info: [13] train-mlogloss:0.05381375175146830 [ Info: [14] train-mlogloss:0.04795372216474442 [ Info: [15] train-mlogloss:0.04319445089924903 [ Info: [16] train-mlogloss:0.03950380216396990 [ Info: [17] train-mlogloss:0.03670381651747794 [ Info: [18] train-mlogloss:0.03451808377036027 [ Info: [19] train-mlogloss:0.03316525518894196 [ Info: [20] train-mlogloss:0.03183717343601442 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97053664582116261 [ Info: [2] train-mlogloss:0.86226033937363400 [ Info: [3] train-mlogloss:0.76999730666478472 [ Info: [4] train-mlogloss:0.69054773194449293 [ Info: [5] train-mlogloss:0.62212099972225365 [ Info: [6] train-mlogloss:0.56257386434645884 [ Info: [7] train-mlogloss:0.51027769645055132 [ Info: [8] train-mlogloss:0.46414213322457815 [ Info: [9] train-mlogloss:0.42327555900528319 [ Info: [10] train-mlogloss:0.38695875065667290 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85236381292343144 [ Info: [2] train-mlogloss:0.67776963881083896 [ Info: [3] train-mlogloss:0.54860250949859624 [ Info: [4] train-mlogloss:0.45131440105892362 [ Info: [5] train-mlogloss:0.37510445685613725 [ Info: [6] train-mlogloss:0.31519275733402796 [ Info: [7] train-mlogloss:0.26763515671094257 [ Info: [8] train-mlogloss:0.22793431225277128 [ Info: [9] train-mlogloss:0.19392670293649036 [ Info: [10] train-mlogloss:0.16588448037703832 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74447296801067531 [ Info: [2] train-mlogloss:0.53441452355611896 [ Info: [3] train-mlogloss:0.39933029668671743 [ Info: [4] train-mlogloss:0.30565242625418165 [ Info: [5] train-mlogloss:0.24001300122056687 [ Info: [6] train-mlogloss:0.18756250668139685 [ Info: [7] train-mlogloss:0.14919329356579553 [ Info: [8] train-mlogloss:0.12055515363102867 [ Info: [9] train-mlogloss:0.09923504747095563 [ Info: [10] train-mlogloss:0.08303172293873061 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97053664582116261 [ Info: [2] train-mlogloss:0.86226033937363400 [ Info: [3] train-mlogloss:0.76999730666478472 [ Info: [4] train-mlogloss:0.69054773194449293 [ Info: [5] train-mlogloss:0.62212099972225365 [ Info: [6] train-mlogloss:0.56257386434645884 [ Info: [7] train-mlogloss:0.51027769645055132 [ Info: [8] train-mlogloss:0.46414213322457815 [ Info: [9] train-mlogloss:0.42327555900528319 [ Info: [10] train-mlogloss:0.38695875065667290 [ Info: [11] train-mlogloss:0.35459378163019817 [ Info: [12] train-mlogloss:0.32567866927101496 [ Info: [13] train-mlogloss:0.29899619846116932 [ Info: [14] train-mlogloss:0.27589764282816931 [ Info: [15] train-mlogloss:0.25514680572918486 [ Info: [16] train-mlogloss:0.23519030951318287 [ Info: [17] train-mlogloss:0.21686726439566839 [ Info: [18] train-mlogloss:0.20033036300114224 [ Info: [19] train-mlogloss:0.18572707488423301 [ Info: [20] train-mlogloss:0.17215918004512787 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85236381292343144 [ Info: [2] train-mlogloss:0.67776963881083896 [ Info: [3] train-mlogloss:0.54860250949859624 [ Info: [4] train-mlogloss:0.45131440105892362 [ Info: [5] train-mlogloss:0.37510445685613725 [ Info: [6] train-mlogloss:0.31519275733402796 [ Info: [7] train-mlogloss:0.26763515671094257 [ Info: [8] train-mlogloss:0.22793431225277128 [ Info: [9] train-mlogloss:0.19392670293649036 [ Info: [10] train-mlogloss:0.16588448037703832 [ Info: [11] train-mlogloss:0.14311025518746603 [ Info: [12] train-mlogloss:0.12478516605638322 [ Info: [13] train-mlogloss:0.10911311578182947 [ Info: [14] train-mlogloss:0.09619074130342120 [ Info: [15] train-mlogloss:0.08540965496074586 [ Info: [16] train-mlogloss:0.07609406060406140 [ Info: [17] train-mlogloss:0.06863283926532382 [ Info: [18] train-mlogloss:0.06200908065906593 [ Info: [19] train-mlogloss:0.05648979984578632 [ Info: [20] train-mlogloss:0.05156948566436768 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74447296801067531 [ Info: [2] train-mlogloss:0.53441452355611896 [ Info: [3] train-mlogloss:0.39933029668671743 [ Info: [4] train-mlogloss:0.30565242625418165 [ Info: [5] train-mlogloss:0.24001300122056687 [ Info: [6] train-mlogloss:0.18756250668139685 [ Info: [7] train-mlogloss:0.14919329356579553 [ Info: [8] train-mlogloss:0.12055515363102867 [ Info: [9] train-mlogloss:0.09923504747095563 [ Info: [10] train-mlogloss:0.08303172293873061 [ Info: [11] train-mlogloss:0.06964252725953148 [ Info: [12] train-mlogloss:0.05983597398513840 [ Info: [13] train-mlogloss:0.05211141916612784 [ Info: [14] train-mlogloss:0.04528380863013722 [ Info: [15] train-mlogloss:0.04068187865472975 [ Info: [16] train-mlogloss:0.03698874328817640 [ Info: [17] train-mlogloss:0.03378712303404297 [ Info: [18] train-mlogloss:0.03146503329986618 [ Info: [19] train-mlogloss:0.02937317864880675 [ Info: [20] train-mlogloss:0.02856659498952684 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96610602935155232 [ Info: [2] train-mlogloss:0.85498510712669007 [ Info: [3] train-mlogloss:0.76048787889026459 [ Info: [4] train-mlogloss:0.67928090947014941 [ Info: [5] train-mlogloss:0.60892528636114940 [ Info: [6] train-mlogloss:0.54757455700919744 [ Info: [7] train-mlogloss:0.49379314042273020 [ Info: [8] train-mlogloss:0.44644049803415936 [ Info: [9] train-mlogloss:0.40459462120419459 [ Info: [10] train-mlogloss:0.36749916076660155 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84391320376169110 [ Info: [2] train-mlogloss:0.66554911306926179 [ Info: [3] train-mlogloss:0.53401708319073626 [ Info: [4] train-mlogloss:0.43405766629037401 [ Info: [5] train-mlogloss:0.35658393388702758 [ Info: [6] train-mlogloss:0.29570389389991758 [ Info: [7] train-mlogloss:0.24758422346342177 [ Info: [8] train-mlogloss:0.20903146536577316 [ Info: [9] train-mlogloss:0.17797896095684596 [ Info: [10] train-mlogloss:0.15274619091124761 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73243870564869473 [ Info: [2] train-mlogloss:0.51898212376094999 [ Info: [3] train-mlogloss:0.38034115774290900 [ Info: [4] train-mlogloss:0.28567313608669098 [ Info: [5] train-mlogloss:0.21936151981353760 [ Info: [6] train-mlogloss:0.17176349248204911 [ Info: [7] train-mlogloss:0.13712078645115808 [ Info: [8] train-mlogloss:0.11157549052011399 [ Info: [9] train-mlogloss:0.09267117757172812 [ Info: [10] train-mlogloss:0.07883728125265667 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96610602935155232 [ Info: [2] train-mlogloss:0.85498510712669007 [ Info: [3] train-mlogloss:0.76048787889026459 [ Info: [4] train-mlogloss:0.67928090947014941 [ Info: [5] train-mlogloss:0.60892528636114940 [ Info: [6] train-mlogloss:0.54757455700919744 [ Info: [7] train-mlogloss:0.49379314042273020 [ Info: [8] train-mlogloss:0.44644049803415936 [ Info: [9] train-mlogloss:0.40459462120419459 [ Info: [10] train-mlogloss:0.36749916076660155 [ Info: [11] train-mlogloss:0.33452646590414503 [ Info: [12] train-mlogloss:0.30514967271259852 [ Info: [13] train-mlogloss:0.27890278838929677 [ Info: [14] train-mlogloss:0.25555970881666457 [ Info: [15] train-mlogloss:0.23463234021550133 [ Info: [16] train-mlogloss:0.21583787770498367 [ Info: [17] train-mlogloss:0.19895084344205402 [ Info: [18] train-mlogloss:0.18373927261148179 [ Info: [19] train-mlogloss:0.17003524615651086 [ Info: [20] train-mlogloss:0.15766795646576653 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84391320376169110 [ Info: [2] train-mlogloss:0.66554911306926179 [ Info: [3] train-mlogloss:0.53401708319073626 [ Info: [4] train-mlogloss:0.43405766629037401 [ Info: [5] train-mlogloss:0.35658393388702758 [ Info: [6] train-mlogloss:0.29570389389991758 [ Info: [7] train-mlogloss:0.24758422346342177 [ Info: [8] train-mlogloss:0.20903146536577316 [ Info: [9] train-mlogloss:0.17797896095684596 [ Info: [10] train-mlogloss:0.15274619091124761 [ Info: [11] train-mlogloss:0.13222991668042683 [ Info: [12] train-mlogloss:0.11548555209523155 [ Info: [13] train-mlogloss:0.10177177552665984 [ Info: [14] train-mlogloss:0.09050260271344866 [ Info: [15] train-mlogloss:0.08121144491292182 [ Info: [16] train-mlogloss:0.07344205808781443 [ Info: [17] train-mlogloss:0.06629338754074914 [ Info: [18] train-mlogloss:0.06077156191070875 [ Info: [19] train-mlogloss:0.05567946622059459 [ Info: [20] train-mlogloss:0.04984344999705042 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73243870564869473 [ Info: [2] train-mlogloss:0.51898212376094999 [ Info: [3] train-mlogloss:0.38034115774290900 [ Info: [4] train-mlogloss:0.28567313608669098 [ Info: [5] train-mlogloss:0.21936151981353760 [ Info: [6] train-mlogloss:0.17176349248204911 [ Info: [7] train-mlogloss:0.13712078645115808 [ Info: [8] train-mlogloss:0.11157549052011399 [ Info: [9] train-mlogloss:0.09267117757172812 [ Info: [10] train-mlogloss:0.07883728125265667 [ Info: [11] train-mlogloss:0.06820655319662321 [ Info: [12] train-mlogloss:0.05997786053589412 [ Info: [13] train-mlogloss:0.05137544002916131 [ Info: [14] train-mlogloss:0.04375683322903656 [ Info: [15] train-mlogloss:0.03998706752345676 [ Info: [16] train-mlogloss:0.03690409193791094 [ Info: [17] train-mlogloss:0.03469347582154331 [ Info: [18] train-mlogloss:0.03213540995937018 [ Info: [19] train-mlogloss:0.03060149953124069 [ Info: [20] train-mlogloss:0.02938025241628999 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97483433712096446 [ Info: [2] train-mlogloss:0.86891427096866425 [ Info: [3] train-mlogloss:0.77857356695901780 [ Info: [4] train-mlogloss:0.69952634062085828 [ Info: [5] train-mlogloss:0.63092502582640875 [ Info: [6] train-mlogloss:0.57102088360559378 [ Info: [7] train-mlogloss:0.51763610981759567 [ Info: [8] train-mlogloss:0.47053923692022054 [ Info: [9] train-mlogloss:0.42884785135587056 [ Info: [10] train-mlogloss:0.39197065773464385 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.86053875173841199 [ Info: [2] train-mlogloss:0.68684130396161758 [ Info: [3] train-mlogloss:0.55817515963599795 [ Info: [4] train-mlogloss:0.45870674649874371 [ Info: [5] train-mlogloss:0.38127541513670060 [ Info: [6] train-mlogloss:0.32041137842904954 [ Info: [7] train-mlogloss:0.27180777419181096 [ Info: [8] train-mlogloss:0.23267553618976047 [ Info: [9] train-mlogloss:0.20129095628148033 [ Info: [10] train-mlogloss:0.17567770828803381 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.75608202389308388 [ Info: [2] train-mlogloss:0.54638213486898513 [ Info: [3] train-mlogloss:0.40748181059246974 [ Info: [4] train-mlogloss:0.31207826903888158 [ Info: [5] train-mlogloss:0.24464475242864517 [ Info: [6] train-mlogloss:0.19644721675486793 [ Info: [7] train-mlogloss:0.16033600306227094 [ Info: [8] train-mlogloss:0.13286803520861126 [ Info: [9] train-mlogloss:0.11189082910617193 [ Info: [10] train-mlogloss:0.09514393306204251 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97483433712096446 [ Info: [2] train-mlogloss:0.86891427096866425 [ Info: [3] train-mlogloss:0.77857356695901780 [ Info: [4] train-mlogloss:0.69952634062085828 [ Info: [5] train-mlogloss:0.63092502582640875 [ Info: [6] train-mlogloss:0.57102088360559378 [ Info: [7] train-mlogloss:0.51763610981759567 [ Info: [8] train-mlogloss:0.47053923692022054 [ Info: [9] train-mlogloss:0.42884785135587056 [ Info: [10] train-mlogloss:0.39197065773464385 [ Info: [11] train-mlogloss:0.35912301824206400 [ Info: [12] train-mlogloss:0.32978181526774453 [ Info: [13] train-mlogloss:0.30351524920690626 [ Info: [14] train-mlogloss:0.27995482143901645 [ Info: [15] train-mlogloss:0.25878425013451350 [ Info: [16] train-mlogloss:0.23973020769300915 [ Info: [17] train-mlogloss:0.22272729419526599 [ Info: [18] train-mlogloss:0.20737572269780294 [ Info: [19] train-mlogloss:0.19322998452754248 [ Info: [20] train-mlogloss:0.18046276157810576 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.86053875173841199 [ Info: [2] train-mlogloss:0.68684130396161758 [ Info: [3] train-mlogloss:0.55817515963599795 [ Info: [4] train-mlogloss:0.45870674649874371 [ Info: [5] train-mlogloss:0.38127541513670060 [ Info: [6] train-mlogloss:0.32041137842904954 [ Info: [7] train-mlogloss:0.27180777419181096 [ Info: [8] train-mlogloss:0.23267553618976047 [ Info: [9] train-mlogloss:0.20129095628148033 [ Info: [10] train-mlogloss:0.17567770828803381 [ Info: [11] train-mlogloss:0.15429947674274444 [ Info: [12] train-mlogloss:0.13697868386904399 [ Info: [13] train-mlogloss:0.12247023121232078 [ Info: [14] train-mlogloss:0.10975979843309948 [ Info: [15] train-mlogloss:0.09853682141928445 [ Info: [16] train-mlogloss:0.08880356592791420 [ Info: [17] train-mlogloss:0.08075196664957773 [ Info: [18] train-mlogloss:0.07382400630130655 [ Info: [19] train-mlogloss:0.06818675989551204 [ Info: [20] train-mlogloss:0.06280734475169863 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.75608202389308388 [ Info: [2] train-mlogloss:0.54638213486898513 [ Info: [3] train-mlogloss:0.40748181059246974 [ Info: [4] train-mlogloss:0.31207826903888158 [ Info: [5] train-mlogloss:0.24464475242864517 [ Info: [6] train-mlogloss:0.19644721675486793 [ Info: [7] train-mlogloss:0.16033600306227094 [ Info: [8] train-mlogloss:0.13286803520861126 [ Info: [9] train-mlogloss:0.11189082910617193 [ Info: [10] train-mlogloss:0.09514393306204251 [ Info: [11] train-mlogloss:0.08188618609593028 [ Info: [12] train-mlogloss:0.07148405427024478 [ Info: [13] train-mlogloss:0.06291855905382406 [ Info: [14] train-mlogloss:0.05675657153839157 [ Info: [15] train-mlogloss:0.05217718592002278 [ Info: [16] train-mlogloss:0.04811737988853738 [ Info: [17] train-mlogloss:0.04479291251904908 [ Info: [18] train-mlogloss:0.04172228531291088 [ Info: [19] train-mlogloss:0.03964075755682730 [ Info: [20] train-mlogloss:0.03830713219053689 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97059223538353334 [ Info: [2] train-mlogloss:0.86283888078871229 [ Info: [3] train-mlogloss:0.77096053588958013 [ Info: [4] train-mlogloss:0.69181114662261234 [ Info: [5] train-mlogloss:0.62304223378499346 [ Info: [6] train-mlogloss:0.56294044823873612 [ Info: [7] train-mlogloss:0.51014076953842524 [ Info: [8] train-mlogloss:0.46354723487581523 [ Info: [9] train-mlogloss:0.42227103738557725 [ Info: [10] train-mlogloss:0.38559732976413907 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85238817476090933 [ Info: [2] train-mlogloss:0.67864443006969632 [ Info: [3] train-mlogloss:0.54987206231980101 [ Info: [4] train-mlogloss:0.45155560175577797 [ Info: [5] train-mlogloss:0.37494158063616073 [ Info: [6] train-mlogloss:0.31229524527277264 [ Info: [7] train-mlogloss:0.26213831986699787 [ Info: [8] train-mlogloss:0.22176577746868134 [ Info: [9] train-mlogloss:0.18904322087764741 [ Info: [10] train-mlogloss:0.16245638728141784 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74437439384914583 [ Info: [2] train-mlogloss:0.53539070799237209 [ Info: [3] train-mlogloss:0.39865371244294301 [ Info: [4] train-mlogloss:0.30156952284631278 [ Info: [5] train-mlogloss:0.23244616034485044 [ Info: [6] train-mlogloss:0.18244187491280692 [ Info: [7] train-mlogloss:0.14632768630981446 [ Info: [8] train-mlogloss:0.11840705829007285 [ Info: [9] train-mlogloss:0.09670401754833403 [ Info: [10] train-mlogloss:0.08028437243331046 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97059223538353334 [ Info: [2] train-mlogloss:0.86283888078871229 [ Info: [3] train-mlogloss:0.77096053588958013 [ Info: [4] train-mlogloss:0.69181114662261234 [ Info: [5] train-mlogloss:0.62304223378499346 [ Info: [6] train-mlogloss:0.56294044823873612 [ Info: [7] train-mlogloss:0.51014076953842524 [ Info: [8] train-mlogloss:0.46354723487581523 [ Info: [9] train-mlogloss:0.42227103738557725 [ Info: [10] train-mlogloss:0.38559732976413907 [ Info: [11] train-mlogloss:0.35180065660249621 [ Info: [12] train-mlogloss:0.32143630215099878 [ Info: [13] train-mlogloss:0.29435623742285227 [ Info: [14] train-mlogloss:0.27015233011472795 [ Info: [15] train-mlogloss:0.24830066022418795 [ Info: [16] train-mlogloss:0.22863553166389466 [ Info: [17] train-mlogloss:0.21091197502045406 [ Info: [18] train-mlogloss:0.19491644359770274 [ Info: [19] train-mlogloss:0.18046211628686815 [ Info: [20] train-mlogloss:0.16743007671265375 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85238817476090933 [ Info: [2] train-mlogloss:0.67864443006969632 [ Info: [3] train-mlogloss:0.54987206231980101 [ Info: [4] train-mlogloss:0.45155560175577797 [ Info: [5] train-mlogloss:0.37494158063616073 [ Info: [6] train-mlogloss:0.31229524527277264 [ Info: [7] train-mlogloss:0.26213831986699787 [ Info: [8] train-mlogloss:0.22176577746868134 [ Info: [9] train-mlogloss:0.18904322087764741 [ Info: [10] train-mlogloss:0.16245638728141784 [ Info: [11] train-mlogloss:0.14103399188745588 [ Info: [12] train-mlogloss:0.12268305867910385 [ Info: [13] train-mlogloss:0.10690229655731293 [ Info: [14] train-mlogloss:0.09379101509139651 [ Info: [15] train-mlogloss:0.08302188011861983 [ Info: [16] train-mlogloss:0.07397217789576167 [ Info: [17] train-mlogloss:0.06665240519103549 [ Info: [18] train-mlogloss:0.06048126412289483 [ Info: [19] train-mlogloss:0.05529815178541910 [ Info: [20] train-mlogloss:0.05090075016376518 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74437439384914583 [ Info: [2] train-mlogloss:0.53539070799237209 [ Info: [3] train-mlogloss:0.39865371244294301 [ Info: [4] train-mlogloss:0.30156952284631278 [ Info: [5] train-mlogloss:0.23244616034485044 [ Info: [6] train-mlogloss:0.18244187491280692 [ Info: [7] train-mlogloss:0.14632768630981446 [ Info: [8] train-mlogloss:0.11840705829007285 [ Info: [9] train-mlogloss:0.09670401754833403 [ Info: [10] train-mlogloss:0.08028437243331046 [ Info: [11] train-mlogloss:0.06792601307942754 [ Info: [12] train-mlogloss:0.05860808754251117 [ Info: [13] train-mlogloss:0.05142338167698610 [ Info: [14] train-mlogloss:0.04472913240038214 [ Info: [15] train-mlogloss:0.03959536069915408 [ Info: [16] train-mlogloss:0.03566983772353047 [ Info: [17] train-mlogloss:0.03238871054102977 [ Info: [18] train-mlogloss:0.02969010223058008 [ Info: [19] train-mlogloss:0.02843482442022789 [ Info: [20] train-mlogloss:0.02735186057786147 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96787397464116409 [ Info: [2] train-mlogloss:0.85801437298456829 [ Info: [3] train-mlogloss:0.76443491265887309 [ Info: [4] train-mlogloss:0.68390247821807859 [ Info: [5] train-mlogloss:0.61404319831303189 [ Info: [6] train-mlogloss:0.55305493388857163 [ Info: [7] train-mlogloss:0.49953319458734424 [ Info: [8] train-mlogloss:0.45234237767401198 [ Info: [9] train-mlogloss:0.41099248642013186 [ Info: [10] train-mlogloss:0.37427794763020106 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84718395074208575 [ Info: [2] train-mlogloss:0.67039029598236088 [ Info: [3] train-mlogloss:0.53964767910185318 [ Info: [4] train-mlogloss:0.44005968088195435 [ Info: [5] train-mlogloss:0.36344064502488999 [ Info: [6] train-mlogloss:0.30093890882673718 [ Info: [7] train-mlogloss:0.25200924021857124 [ Info: [8] train-mlogloss:0.21243283819584619 [ Info: [9] train-mlogloss:0.18046860482011523 [ Info: [10] train-mlogloss:0.15451039572556813 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73693051394962128 [ Info: [2] train-mlogloss:0.52478807568550112 [ Info: [3] train-mlogloss:0.38649080679530190 [ Info: [4] train-mlogloss:0.29264650855745589 [ Info: [5] train-mlogloss:0.22279193089121863 [ Info: [6] train-mlogloss:0.17482217663810368 [ Info: [7] train-mlogloss:0.13868026215405690 [ Info: [8] train-mlogloss:0.11248991822912580 [ Info: [9] train-mlogloss:0.09305882922240666 [ Info: [10] train-mlogloss:0.07911519376294954 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96787397464116409 [ Info: [2] train-mlogloss:0.85801437298456829 [ Info: [3] train-mlogloss:0.76443491265887309 [ Info: [4] train-mlogloss:0.68390247821807859 [ Info: [5] train-mlogloss:0.61404319831303189 [ Info: [6] train-mlogloss:0.55305493388857163 [ Info: [7] train-mlogloss:0.49953319458734424 [ Info: [8] train-mlogloss:0.45234237767401198 [ Info: [9] train-mlogloss:0.41099248642013186 [ Info: [10] train-mlogloss:0.37427794763020106 [ Info: [11] train-mlogloss:0.34045737896646772 [ Info: [12] train-mlogloss:0.31034598747889203 [ Info: [13] train-mlogloss:0.28382870157559714 [ Info: [14] train-mlogloss:0.26008744466872441 [ Info: [15] train-mlogloss:0.23851433751128970 [ Info: [16] train-mlogloss:0.21921068628629048 [ Info: [17] train-mlogloss:0.20184177245412555 [ Info: [18] train-mlogloss:0.18619344660214016 [ Info: [19] train-mlogloss:0.17207835047017961 [ Info: [20] train-mlogloss:0.15933201965831575 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84718395074208575 [ Info: [2] train-mlogloss:0.67039029598236088 [ Info: [3] train-mlogloss:0.53964767910185318 [ Info: [4] train-mlogloss:0.44005968088195435 [ Info: [5] train-mlogloss:0.36344064502488999 [ Info: [6] train-mlogloss:0.30093890882673718 [ Info: [7] train-mlogloss:0.25200924021857124 [ Info: [8] train-mlogloss:0.21243283819584619 [ Info: [9] train-mlogloss:0.18046860482011523 [ Info: [10] train-mlogloss:0.15451039572556813 [ Info: [11] train-mlogloss:0.13364208979266032 [ Info: [12] train-mlogloss:0.11658473483153751 [ Info: [13] train-mlogloss:0.10256962215616590 [ Info: [14] train-mlogloss:0.09153323570887248 [ Info: [15] train-mlogloss:0.08050647956274805 [ Info: [16] train-mlogloss:0.07164909938971202 [ Info: [17] train-mlogloss:0.06380777234832445 [ Info: [18] train-mlogloss:0.05690975148408186 [ Info: [19] train-mlogloss:0.05123861400144441 [ Info: [20] train-mlogloss:0.04678891239066919 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73693051394962128 [ Info: [2] train-mlogloss:0.52478807568550112 [ Info: [3] train-mlogloss:0.38649080679530190 [ Info: [4] train-mlogloss:0.29264650855745589 [ Info: [5] train-mlogloss:0.22279193089121863 [ Info: [6] train-mlogloss:0.17482217663810368 [ Info: [7] train-mlogloss:0.13868026215405690 [ Info: [8] train-mlogloss:0.11248991822912580 [ Info: [9] train-mlogloss:0.09305882922240666 [ Info: [10] train-mlogloss:0.07911519376294954 [ Info: [11] train-mlogloss:0.06609121280766669 [ Info: [12] train-mlogloss:0.05719876220183713 [ Info: [13] train-mlogloss:0.04861812774269354 [ Info: [14] train-mlogloss:0.04282568136141414 [ Info: [15] train-mlogloss:0.03820490874350071 [ Info: [16] train-mlogloss:0.03419186977580899 [ Info: [17] train-mlogloss:0.03123849136311383 [ Info: [18] train-mlogloss:0.02861831176671244 [ Info: [19] train-mlogloss:0.02694900300176371 [ Info: [20] train-mlogloss:0.02599575585197835 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96700005474544704 [ Info: [2] train-mlogloss:0.85659597033546087 [ Info: [3] train-mlogloss:0.76268606923875359 [ Info: [4] train-mlogloss:0.68196817636489870 [ Info: [5] train-mlogloss:0.61202497539066136 [ Info: [6] train-mlogloss:0.55102541446685793 [ Info: [7] train-mlogloss:0.49754521790004913 [ Info: [8] train-mlogloss:0.45032977291515897 [ Info: [9] train-mlogloss:0.40856265624364219 [ Info: [10] train-mlogloss:0.37149838436217536 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84562079225267683 [ Info: [2] train-mlogloss:0.66834616831370763 [ Info: [3] train-mlogloss:0.53756816160111198 [ Info: [4] train-mlogloss:0.43793557343028838 [ Info: [5] train-mlogloss:0.36054984387897310 [ Info: [6] train-mlogloss:0.29967187784966970 [ Info: [7] train-mlogloss:0.25119291827792212 [ Info: [8] train-mlogloss:0.21227479378382366 [ Info: [9] train-mlogloss:0.18082824079763321 [ Info: [10] train-mlogloss:0.15528092519158410 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73487439780008224 [ Info: [2] train-mlogloss:0.52264665365219121 [ Info: [3] train-mlogloss:0.38434811348006837 [ Info: [4] train-mlogloss:0.28958687668754940 [ Info: [5] train-mlogloss:0.22269679307937623 [ Info: [6] train-mlogloss:0.17452047041484287 [ Info: [7] train-mlogloss:0.13933121483950389 [ Info: [8] train-mlogloss:0.11334160495372046 [ Info: [9] train-mlogloss:0.09385201711030233 [ Info: [10] train-mlogloss:0.07878754451161339 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96700005474544704 [ Info: [2] train-mlogloss:0.85659597033546087 [ Info: [3] train-mlogloss:0.76268606923875359 [ Info: [4] train-mlogloss:0.68196817636489870 [ Info: [5] train-mlogloss:0.61202497539066136 [ Info: [6] train-mlogloss:0.55102541446685793 [ Info: [7] train-mlogloss:0.49754521790004913 [ Info: [8] train-mlogloss:0.45032977291515897 [ Info: [9] train-mlogloss:0.40856265624364219 [ Info: [10] train-mlogloss:0.37149838436217536 [ Info: [11] train-mlogloss:0.33851786937032430 [ Info: [12] train-mlogloss:0.30912666604632422 [ Info: [13] train-mlogloss:0.28284756796700616 [ Info: [14] train-mlogloss:0.25930682363964264 [ Info: [15] train-mlogloss:0.23818368117014568 [ Info: [16] train-mlogloss:0.21920108341035388 [ Info: [17] train-mlogloss:0.20211852803116753 [ Info: [18] train-mlogloss:0.18672612877119155 [ Info: [19] train-mlogloss:0.17284025223482222 [ Info: [20] train-mlogloss:0.16029964103585198 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84562079225267683 [ Info: [2] train-mlogloss:0.66834616831370763 [ Info: [3] train-mlogloss:0.53756816160111198 [ Info: [4] train-mlogloss:0.43793557343028838 [ Info: [5] train-mlogloss:0.36054984387897310 [ Info: [6] train-mlogloss:0.29967187784966970 [ Info: [7] train-mlogloss:0.25119291827792212 [ Info: [8] train-mlogloss:0.21227479378382366 [ Info: [9] train-mlogloss:0.18082824079763321 [ Info: [10] train-mlogloss:0.15528092519158410 [ Info: [11] train-mlogloss:0.13442861444893336 [ Info: [12] train-mlogloss:0.11746168250129337 [ Info: [13] train-mlogloss:0.10323805567764101 [ Info: [14] train-mlogloss:0.09138539497341429 [ Info: [15] train-mlogloss:0.08143110108517465 [ Info: [16] train-mlogloss:0.07314958409184501 [ Info: [17] train-mlogloss:0.06555956257950692 [ Info: [18] train-mlogloss:0.05912817705954824 [ Info: [19] train-mlogloss:0.05410789453557559 [ Info: [20] train-mlogloss:0.04868868859041305 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73487439780008224 [ Info: [2] train-mlogloss:0.52264665365219121 [ Info: [3] train-mlogloss:0.38434811348006837 [ Info: [4] train-mlogloss:0.28958687668754940 [ Info: [5] train-mlogloss:0.22269679307937623 [ Info: [6] train-mlogloss:0.17452047041484287 [ Info: [7] train-mlogloss:0.13933121483950389 [ Info: [8] train-mlogloss:0.11334160495372046 [ Info: [9] train-mlogloss:0.09385201711030233 [ Info: [10] train-mlogloss:0.07878754451161339 [ Info: [11] train-mlogloss:0.06736134407775743 [ Info: [12] train-mlogloss:0.05762513616964931 [ Info: [13] train-mlogloss:0.05070862894256910 [ Info: [14] train-mlogloss:0.04366399539368493 [ Info: [15] train-mlogloss:0.03890408116082351 [ Info: [16] train-mlogloss:0.03606735062563703 [ Info: [17] train-mlogloss:0.03287566354764360 [ Info: [18] train-mlogloss:0.03063989431552944 [ Info: [19] train-mlogloss:0.02877358081972315 [ Info: [20] train-mlogloss:0.02799010152618090 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96585079431533816 [ Info: [2] train-mlogloss:0.85444615057536533 [ Info: [3] train-mlogloss:0.75966438736234387 [ Info: [4] train-mlogloss:0.67949670609973722 [ Info: [5] train-mlogloss:0.60993991579328266 [ Info: [6] train-mlogloss:0.54921302852176490 [ Info: [7] train-mlogloss:0.49590954354831152 [ Info: [8] train-mlogloss:0.44938316089766367 [ Info: [9] train-mlogloss:0.40816288732347034 [ Info: [10] train-mlogloss:0.37159543150947205 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84338867437271847 [ Info: [2] train-mlogloss:0.66444503068923955 [ Info: [3] train-mlogloss:0.53453910748163858 [ Info: [4] train-mlogloss:0.43647313231513613 [ Info: [5] train-mlogloss:0.36024566150846937 [ Info: [6] train-mlogloss:0.30003022239321753 [ Info: [7] train-mlogloss:0.25218097042469750 [ Info: [8] train-mlogloss:0.21356762661820367 [ Info: [9] train-mlogloss:0.18241059482097627 [ Info: [10] train-mlogloss:0.15704269962651388 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73163095996493388 [ Info: [2] train-mlogloss:0.52062735415640327 [ Info: [3] train-mlogloss:0.38427388696443465 [ Info: [4] train-mlogloss:0.29056968121301563 [ Info: [5] train-mlogloss:0.22448490389755793 [ Info: [6] train-mlogloss:0.17673828388963428 [ Info: [7] train-mlogloss:0.14174743443727494 [ Info: [8] train-mlogloss:0.11511904625665574 [ Info: [9] train-mlogloss:0.09422411641904287 [ Info: [10] train-mlogloss:0.07873683823716073 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96585079431533816 [ Info: [2] train-mlogloss:0.85444615057536533 [ Info: [3] train-mlogloss:0.75966438736234387 [ Info: [4] train-mlogloss:0.67949670609973722 [ Info: [5] train-mlogloss:0.60993991579328266 [ Info: [6] train-mlogloss:0.54921302852176490 [ Info: [7] train-mlogloss:0.49590954354831152 [ Info: [8] train-mlogloss:0.44938316089766367 [ Info: [9] train-mlogloss:0.40816288732347034 [ Info: [10] train-mlogloss:0.37159543150947205 [ Info: [11] train-mlogloss:0.33898655970891317 [ Info: [12] train-mlogloss:0.30989036219460625 [ Info: [13] train-mlogloss:0.28388718253090267 [ Info: [14] train-mlogloss:0.26062943296773095 [ Info: [15] train-mlogloss:0.23968199888865152 [ Info: [16] train-mlogloss:0.22089106454735710 [ Info: [17] train-mlogloss:0.20396611364114853 [ Info: [18] train-mlogloss:0.18869644971120925 [ Info: [19] train-mlogloss:0.17490849296251934 [ Info: [20] train-mlogloss:0.16243904559385208 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84338867437271847 [ Info: [2] train-mlogloss:0.66444503068923955 [ Info: [3] train-mlogloss:0.53453910748163858 [ Info: [4] train-mlogloss:0.43647313231513613 [ Info: [5] train-mlogloss:0.36024566150846937 [ Info: [6] train-mlogloss:0.30003022239321753 [ Info: [7] train-mlogloss:0.25218097042469750 [ Info: [8] train-mlogloss:0.21356762661820367 [ Info: [9] train-mlogloss:0.18241059482097627 [ Info: [10] train-mlogloss:0.15704269962651388 [ Info: [11] train-mlogloss:0.13628876209259033 [ Info: [12] train-mlogloss:0.11910255302985509 [ Info: [13] train-mlogloss:0.10395244090330033 [ Info: [14] train-mlogloss:0.09155227144559225 [ Info: [15] train-mlogloss:0.08176742543776830 [ Info: [16] train-mlogloss:0.07343967432777086 [ Info: [17] train-mlogloss:0.06623131171578453 [ Info: [18] train-mlogloss:0.06022861394144240 [ Info: [19] train-mlogloss:0.05509491610739913 [ Info: [20] train-mlogloss:0.05068094647001652 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73163095996493388 [ Info: [2] train-mlogloss:0.52062735415640327 [ Info: [3] train-mlogloss:0.38427388696443465 [ Info: [4] train-mlogloss:0.29056968121301563 [ Info: [5] train-mlogloss:0.22448490389755793 [ Info: [6] train-mlogloss:0.17673828388963428 [ Info: [7] train-mlogloss:0.14174743443727494 [ Info: [8] train-mlogloss:0.11511904625665574 [ Info: [9] train-mlogloss:0.09422411641904287 [ Info: [10] train-mlogloss:0.07873683823716073 [ Info: [11] train-mlogloss:0.06720068830819358 [ Info: [12] train-mlogloss:0.05818869201909928 [ Info: [13] train-mlogloss:0.05106416612508751 [ Info: [14] train-mlogloss:0.04545247785392262 [ Info: [15] train-mlogloss:0.04142380009094874 [ Info: [16] train-mlogloss:0.03817441137064071 [ Info: [17] train-mlogloss:0.03579025570125807 [ Info: [18] train-mlogloss:0.03350829133497817 [ Info: [19] train-mlogloss:0.03166526316532067 [ Info: [20] train-mlogloss:0.03063917809299060 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97314797128949848 [ Info: [2] train-mlogloss:0.86725684177307860 [ Info: [3] train-mlogloss:0.77668579362687606 [ Info: [4] train-mlogloss:0.69847365333920430 [ Info: [5] train-mlogloss:0.63041323536918281 [ Info: [6] train-mlogloss:0.57081801550728939 [ Info: [7] train-mlogloss:0.51651351537023271 [ Info: [8] train-mlogloss:0.46860549733752294 [ Info: [9] train-mlogloss:0.42604469969159081 [ Info: [10] train-mlogloss:0.38836861252784727 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85713134266081314 [ Info: [2] train-mlogloss:0.68571359884171257 [ Info: [3] train-mlogloss:0.55802064963749476 [ Info: [4] train-mlogloss:0.45673101657912846 [ Info: [5] train-mlogloss:0.37784429107393536 [ Info: [6] train-mlogloss:0.31558467518715633 [ Info: [7] train-mlogloss:0.26591874616486688 [ Info: [8] train-mlogloss:0.22621544230551946 [ Info: [9] train-mlogloss:0.19371936732814427 [ Info: [10] train-mlogloss:0.16711152536528451 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.75091142824717927 [ Info: [2] train-mlogloss:0.54388612281708493 [ Info: [3] train-mlogloss:0.40275605292547317 [ Info: [4] train-mlogloss:0.30574866079148794 [ Info: [5] train-mlogloss:0.23698939865543728 [ Info: [6] train-mlogloss:0.18726269304752349 [ Info: [7] train-mlogloss:0.15043453481935321 [ Info: [8] train-mlogloss:0.12229952492884227 [ Info: [9] train-mlogloss:0.10179623805341266 [ Info: [10] train-mlogloss:0.08609343469142913 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97314797128949848 [ Info: [2] train-mlogloss:0.86725684177307860 [ Info: [3] train-mlogloss:0.77668579362687606 [ Info: [4] train-mlogloss:0.69847365333920430 [ Info: [5] train-mlogloss:0.63041323536918281 [ Info: [6] train-mlogloss:0.57081801550728939 [ Info: [7] train-mlogloss:0.51651351537023271 [ Info: [8] train-mlogloss:0.46860549733752294 [ Info: [9] train-mlogloss:0.42604469969159081 [ Info: [10] train-mlogloss:0.38836861252784727 [ Info: [11] train-mlogloss:0.35479994018872579 [ Info: [12] train-mlogloss:0.32481490543910435 [ Info: [13] train-mlogloss:0.29798226470039002 [ Info: [14] train-mlogloss:0.27390729770773931 [ Info: [15] train-mlogloss:0.25244823708420711 [ Info: [16] train-mlogloss:0.23310880604244413 [ Info: [17] train-mlogloss:0.21554808432147615 [ Info: [18] train-mlogloss:0.19965294443425677 [ Info: [19] train-mlogloss:0.18525580394835700 [ Info: [20] train-mlogloss:0.17189127036503382 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85713134266081314 [ Info: [2] train-mlogloss:0.68571359884171257 [ Info: [3] train-mlogloss:0.55802064963749476 [ Info: [4] train-mlogloss:0.45673101657912846 [ Info: [5] train-mlogloss:0.37784429107393536 [ Info: [6] train-mlogloss:0.31558467518715633 [ Info: [7] train-mlogloss:0.26591874616486688 [ Info: [8] train-mlogloss:0.22621544230551946 [ Info: [9] train-mlogloss:0.19371936732814427 [ Info: [10] train-mlogloss:0.16711152536528451 [ Info: [11] train-mlogloss:0.14471447907742999 [ Info: [12] train-mlogloss:0.12652544542437508 [ Info: [13] train-mlogloss:0.11159505077770777 [ Info: [14] train-mlogloss:0.09920312531647228 [ Info: [15] train-mlogloss:0.08879963226971171 [ Info: [16] train-mlogloss:0.08020201612796102 [ Info: [17] train-mlogloss:0.07275149683867183 [ Info: [18] train-mlogloss:0.06652590628890764 [ Info: [19] train-mlogloss:0.06111020662245296 [ Info: [20] train-mlogloss:0.05664906331471035 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.75091142824717927 [ Info: [2] train-mlogloss:0.54388612281708493 [ Info: [3] train-mlogloss:0.40275605292547317 [ Info: [4] train-mlogloss:0.30574866079148794 [ Info: [5] train-mlogloss:0.23698939865543728 [ Info: [6] train-mlogloss:0.18726269304752349 [ Info: [7] train-mlogloss:0.15043453481935321 [ Info: [8] train-mlogloss:0.12229952492884227 [ Info: [9] train-mlogloss:0.10179623805341266 [ Info: [10] train-mlogloss:0.08609343469142913 [ Info: [11] train-mlogloss:0.07408291718789510 [ Info: [12] train-mlogloss:0.06443484113329932 [ Info: [13] train-mlogloss:0.05714751265588261 [ Info: [14] train-mlogloss:0.05137462413736752 [ Info: [15] train-mlogloss:0.04579867780918167 [ Info: [16] train-mlogloss:0.04211297569175562 [ Info: [17] train-mlogloss:0.03841374248621009 [ Info: [18] train-mlogloss:0.03598289958955277 [ Info: [19] train-mlogloss:0.03374387554469563 [ Info: [20] train-mlogloss:0.03242568272565093 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96811607678731282 [ Info: [2] train-mlogloss:0.85874129533767696 [ Info: [3] train-mlogloss:0.76575939307610197 [ Info: [4] train-mlogloss:0.68587076663970947 [ Info: [5] train-mlogloss:0.61666562507549927 [ Info: [6] train-mlogloss:0.55632219513257342 [ Info: [7] train-mlogloss:0.50342544466257100 [ Info: [8] train-mlogloss:0.45685214449961981 [ Info: [9] train-mlogloss:0.41569464256366095 [ Info: [10] train-mlogloss:0.37920861095190050 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84781805475552874 [ Info: [2] train-mlogloss:0.67235508114099507 [ Info: [3] train-mlogloss:0.54299825827280679 [ Info: [4] train-mlogloss:0.44469709595044454 [ Info: [5] train-mlogloss:0.36850536366303760 [ Info: [6] train-mlogloss:0.30862711568673451 [ Info: [7] train-mlogloss:0.26108740468819935 [ Info: [8] train-mlogloss:0.22304861148198446 [ Info: [9] train-mlogloss:0.19242397199074426 [ Info: [10] train-mlogloss:0.16764446422457696 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73811481495698295 [ Info: [2] train-mlogloss:0.52821869552135470 [ Info: [3] train-mlogloss:0.39189766099055606 [ Info: [4] train-mlogloss:0.29879944771528244 [ Info: [5] train-mlogloss:0.23334996874133745 [ Info: [6] train-mlogloss:0.18646645744641621 [ Info: [7] train-mlogloss:0.15243681917587917 [ Info: [8] train-mlogloss:0.12748876189192135 [ Info: [9] train-mlogloss:0.10511573186765115 [ Info: [10] train-mlogloss:0.08821864034980535 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96811607678731282 [ Info: [2] train-mlogloss:0.85874129533767696 [ Info: [3] train-mlogloss:0.76575939307610197 [ Info: [4] train-mlogloss:0.68587076663970947 [ Info: [5] train-mlogloss:0.61666562507549927 [ Info: [6] train-mlogloss:0.55632219513257342 [ Info: [7] train-mlogloss:0.50342544466257100 [ Info: [8] train-mlogloss:0.45685214449961981 [ Info: [9] train-mlogloss:0.41569464256366095 [ Info: [10] train-mlogloss:0.37920861095190050 [ Info: [11] train-mlogloss:0.34677631705999373 [ Info: [12] train-mlogloss:0.31787988593180977 [ Info: [13] train-mlogloss:0.29208092192808788 [ Info: [14] train-mlogloss:0.26900569722056389 [ Info: [15] train-mlogloss:0.24833342432975769 [ Info: [16] train-mlogloss:0.22978737975160282 [ Info: [17] train-mlogloss:0.21312705154220263 [ Info: [18] train-mlogloss:0.19814322069287299 [ Info: [19] train-mlogloss:0.18465255101521810 [ Info: [20] train-mlogloss:0.17249404688676198 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84781805475552874 [ Info: [2] train-mlogloss:0.67235508114099507 [ Info: [3] train-mlogloss:0.54299825827280679 [ Info: [4] train-mlogloss:0.44469709595044454 [ Info: [5] train-mlogloss:0.36850536366303760 [ Info: [6] train-mlogloss:0.30862711568673451 [ Info: [7] train-mlogloss:0.26108740468819935 [ Info: [8] train-mlogloss:0.22304861148198446 [ Info: [9] train-mlogloss:0.19242397199074426 [ Info: [10] train-mlogloss:0.16764446422457696 [ Info: [11] train-mlogloss:0.14750947381059329 [ Info: [12] train-mlogloss:0.13108780470987161 [ Info: [13] train-mlogloss:0.11585131194442511 [ Info: [14] train-mlogloss:0.10237029846757650 [ Info: [15] train-mlogloss:0.09116067799429099 [ Info: [16] train-mlogloss:0.08228460174674788 [ Info: [17] train-mlogloss:0.07480527786538005 [ Info: [18] train-mlogloss:0.06767710566831132 [ Info: [19] train-mlogloss:0.06143433291775485 [ Info: [20] train-mlogloss:0.05613800777743260 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73811481495698295 [ Info: [2] train-mlogloss:0.52821869552135470 [ Info: [3] train-mlogloss:0.39189766099055606 [ Info: [4] train-mlogloss:0.29879944771528244 [ Info: [5] train-mlogloss:0.23334996874133745 [ Info: [6] train-mlogloss:0.18646645744641621 [ Info: [7] train-mlogloss:0.15243681917587917 [ Info: [8] train-mlogloss:0.12748876189192135 [ Info: [9] train-mlogloss:0.10511573186765115 [ Info: [10] train-mlogloss:0.08821864034980535 [ Info: [11] train-mlogloss:0.07599299754947424 [ Info: [12] train-mlogloss:0.06530090995753805 [ Info: [13] train-mlogloss:0.05663066773364941 [ Info: [14] train-mlogloss:0.04993736871207754 [ Info: [15] train-mlogloss:0.04466134159204860 [ Info: [16] train-mlogloss:0.03985112536077698 [ Info: [17] train-mlogloss:0.03695193907866876 [ Info: [18] train-mlogloss:0.03438642539549619 [ Info: [19] train-mlogloss:0.03216321163345128 [ Info: [20] train-mlogloss:0.03090460280266901 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96833887745936709 [ Info: [2] train-mlogloss:0.85902396092812217 [ Info: [3] train-mlogloss:0.76598539700110757 [ Info: [4] train-mlogloss:0.68595308115084963 [ Info: [5] train-mlogloss:0.61653779049714408 [ Info: [6] train-mlogloss:0.55593291868766148 [ Info: [7] train-mlogloss:0.50273480142156279 [ Info: [8] train-mlogloss:0.45580217887957891 [ Info: [9] train-mlogloss:0.41424685095747310 [ Info: [10] train-mlogloss:0.37734439000487330 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84815710137287781 [ Info: [2] train-mlogloss:0.67247525105873740 [ Info: [3] train-mlogloss:0.54261388132969535 [ Info: [4] train-mlogloss:0.44364584510525068 [ Info: [5] train-mlogloss:0.36657707542181017 [ Info: [6] train-mlogloss:0.30581350997090340 [ Info: [7] train-mlogloss:0.25734554802378018 [ Info: [8] train-mlogloss:0.21840556388099988 [ Info: [9] train-mlogloss:0.18685293942689896 [ Info: [10] train-mlogloss:0.16113669859866300 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73845412035783131 [ Info: [2] train-mlogloss:0.52783957645297053 [ Info: [3] train-mlogloss:0.39034805794556937 [ Info: [4] train-mlogloss:0.29584019382794696 [ Info: [5] train-mlogloss:0.22888177024821441 [ Info: [6] train-mlogloss:0.18053050128122169 [ Info: [7] train-mlogloss:0.14504916090518236 [ Info: [8] train-mlogloss:0.11847786009311675 [ Info: [9] train-mlogloss:0.09896949430306752 [ Info: [10] train-mlogloss:0.08397884381314119 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96833887745936709 [ Info: [2] train-mlogloss:0.85902396092812217 [ Info: [3] train-mlogloss:0.76598539700110757 [ Info: [4] train-mlogloss:0.68595308115084963 [ Info: [5] train-mlogloss:0.61653779049714408 [ Info: [6] train-mlogloss:0.55593291868766148 [ Info: [7] train-mlogloss:0.50273480142156279 [ Info: [8] train-mlogloss:0.45580217887957891 [ Info: [9] train-mlogloss:0.41424685095747310 [ Info: [10] train-mlogloss:0.37734439000487330 [ Info: [11] train-mlogloss:0.34448810865481694 [ Info: [12] train-mlogloss:0.31515217572450638 [ Info: [13] train-mlogloss:0.28891005789240204 [ Info: [14] train-mlogloss:0.26537989825010300 [ Info: [15] train-mlogloss:0.24427802699307602 [ Info: [16] train-mlogloss:0.22529004750152429 [ Info: [17] train-mlogloss:0.20817923719684284 [ Info: [18] train-mlogloss:0.19273905952771506 [ Info: [19] train-mlogloss:0.17878887094557286 [ Info: [20] train-mlogloss:0.16616982370615005 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84815710137287781 [ Info: [2] train-mlogloss:0.67247525105873740 [ Info: [3] train-mlogloss:0.54261388132969535 [ Info: [4] train-mlogloss:0.44364584510525068 [ Info: [5] train-mlogloss:0.36657707542181017 [ Info: [6] train-mlogloss:0.30581350997090340 [ Info: [7] train-mlogloss:0.25734554802378018 [ Info: [8] train-mlogloss:0.21840556388099988 [ Info: [9] train-mlogloss:0.18685293942689896 [ Info: [10] train-mlogloss:0.16113669859866300 [ Info: [11] train-mlogloss:0.14033950592080752 [ Info: [12] train-mlogloss:0.12283528124292692 [ Info: [13] train-mlogloss:0.10867690214266380 [ Info: [14] train-mlogloss:0.09685204128424327 [ Info: [15] train-mlogloss:0.08672408579538265 [ Info: [16] train-mlogloss:0.07851348665232459 [ Info: [17] train-mlogloss:0.07132942859704296 [ Info: [18] train-mlogloss:0.06508564778293173 [ Info: [19] train-mlogloss:0.05957514435673753 [ Info: [20] train-mlogloss:0.05488395773184796 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73845412035783131 [ Info: [2] train-mlogloss:0.52783957645297053 [ Info: [3] train-mlogloss:0.39034805794556937 [ Info: [4] train-mlogloss:0.29584019382794696 [ Info: [5] train-mlogloss:0.22888177024821441 [ Info: [6] train-mlogloss:0.18053050128122169 [ Info: [7] train-mlogloss:0.14504916090518236 [ Info: [8] train-mlogloss:0.11847786009311675 [ Info: [9] train-mlogloss:0.09896949430306752 [ Info: [10] train-mlogloss:0.08397884381314119 [ Info: [11] train-mlogloss:0.07174617716421684 [ Info: [12] train-mlogloss:0.06286315557857354 [ Info: [13] train-mlogloss:0.05532454738082985 [ Info: [14] train-mlogloss:0.04974799879516165 [ Info: [15] train-mlogloss:0.04549007653258741 [ Info: [16] train-mlogloss:0.04165570423938334 [ Info: [17] train-mlogloss:0.03914229395644118 [ Info: [18] train-mlogloss:0.03669908528681844 [ Info: [19] train-mlogloss:0.03460796894505620 [ Info: [20] train-mlogloss:0.03348505302177121 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97108292877674107 [ Info: [2] train-mlogloss:0.86395158569018049 [ Info: [3] train-mlogloss:0.77270135929187134 [ Info: [4] train-mlogloss:0.69411528309186299 [ Info: [5] train-mlogloss:0.62589055697123208 [ Info: [6] train-mlogloss:0.56626809785763421 [ Info: [7] train-mlogloss:0.51387220546603207 [ Info: [8] train-mlogloss:0.46762366642554604 [ Info: [9] train-mlogloss:0.42663268471757571 [ Info: [10] train-mlogloss:0.38959423080086708 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85342752238114672 [ Info: [2] train-mlogloss:0.68106268147627513 [ Info: [3] train-mlogloss:0.55327483812967937 [ Info: [4] train-mlogloss:0.45573931286732355 [ Info: [5] train-mlogloss:0.37965293824672697 [ Info: [6] train-mlogloss:0.31709163884321850 [ Info: [7] train-mlogloss:0.26818285758296651 [ Info: [8] train-mlogloss:0.22765159669021764 [ Info: [9] train-mlogloss:0.19475929439067841 [ Info: [10] train-mlogloss:0.16790664742390315 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74602477997541428 [ Info: [2] train-mlogloss:0.53888657266894979 [ Info: [3] train-mlogloss:0.40343489125370979 [ Info: [4] train-mlogloss:0.30795478100577989 [ Info: [5] train-mlogloss:0.23950284346938133 [ Info: [6] train-mlogloss:0.18933882539470989 [ Info: [7] train-mlogloss:0.15241098161786795 [ Info: [8] train-mlogloss:0.12462584407379231 [ Info: [9] train-mlogloss:0.10305530956635872 [ Info: [10] train-mlogloss:0.08716537660608689 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97108292877674107 [ Info: [2] train-mlogloss:0.86395158569018049 [ Info: [3] train-mlogloss:0.77270135929187134 [ Info: [4] train-mlogloss:0.69411528309186299 [ Info: [5] train-mlogloss:0.62589055697123208 [ Info: [6] train-mlogloss:0.56626809785763421 [ Info: [7] train-mlogloss:0.51387220546603207 [ Info: [8] train-mlogloss:0.46762366642554604 [ Info: [9] train-mlogloss:0.42663268471757571 [ Info: [10] train-mlogloss:0.38959423080086708 [ Info: [11] train-mlogloss:0.35659764334559441 [ Info: [12] train-mlogloss:0.32710295965274178 [ Info: [13] train-mlogloss:0.30066605086127918 [ Info: [14] train-mlogloss:0.27676568205157914 [ Info: [15] train-mlogloss:0.25530398016174632 [ Info: [16] train-mlogloss:0.23557980445524057 [ Info: [17] train-mlogloss:0.21779147957762082 [ Info: [18] train-mlogloss:0.20172635403772196 [ Info: [19] train-mlogloss:0.18719860936204594 [ Info: [20] train-mlogloss:0.17404481284320356 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85342752238114672 [ Info: [2] train-mlogloss:0.68106268147627513 [ Info: [3] train-mlogloss:0.55327483812967937 [ Info: [4] train-mlogloss:0.45573931286732355 [ Info: [5] train-mlogloss:0.37965293824672697 [ Info: [6] train-mlogloss:0.31709163884321850 [ Info: [7] train-mlogloss:0.26818285758296651 [ Info: [8] train-mlogloss:0.22765159669021764 [ Info: [9] train-mlogloss:0.19475929439067841 [ Info: [10] train-mlogloss:0.16790664742390315 [ Info: [11] train-mlogloss:0.14553643427789212 [ Info: [12] train-mlogloss:0.12700240351259709 [ Info: [13] train-mlogloss:0.11170199941843748 [ Info: [14] train-mlogloss:0.09901579236611724 [ Info: [15] train-mlogloss:0.08876700187101960 [ Info: [16] train-mlogloss:0.08027175264433026 [ Info: [17] train-mlogloss:0.07283595850070318 [ Info: [18] train-mlogloss:0.06669970432606837 [ Info: [19] train-mlogloss:0.06125536652592321 [ Info: [20] train-mlogloss:0.05626023228590687 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74602477997541428 [ Info: [2] train-mlogloss:0.53888657266894979 [ Info: [3] train-mlogloss:0.40343489125370979 [ Info: [4] train-mlogloss:0.30795478100577989 [ Info: [5] train-mlogloss:0.23950284346938133 [ Info: [6] train-mlogloss:0.18933882539470989 [ Info: [7] train-mlogloss:0.15241098161786795 [ Info: [8] train-mlogloss:0.12462584407379231 [ Info: [9] train-mlogloss:0.10305530956635872 [ Info: [10] train-mlogloss:0.08716537660608689 [ Info: [11] train-mlogloss:0.07504897192120552 [ Info: [12] train-mlogloss:0.06534680733457207 [ Info: [13] train-mlogloss:0.05704669187155863 [ Info: [14] train-mlogloss:0.05036235641067226 [ Info: [15] train-mlogloss:0.04595253494723390 [ Info: [16] train-mlogloss:0.04234977451463540 [ Info: [17] train-mlogloss:0.03915340924480309 [ Info: [18] train-mlogloss:0.03669215199382355 [ Info: [19] train-mlogloss:0.03431193712943544 [ Info: [20] train-mlogloss:0.03284359301906079 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97044846167167031 [ Info: [2] train-mlogloss:0.86026118844747546 [ Info: [3] train-mlogloss:0.76653815011183424 [ Info: [4] train-mlogloss:0.68597821046908691 [ Info: [5] train-mlogloss:0.61655587951342261 [ Info: [6] train-mlogloss:0.55598993450403211 [ Info: [7] train-mlogloss:0.50286740536491081 [ Info: [8] train-mlogloss:0.45606419419248900 [ Info: [9] train-mlogloss:0.41467392817139626 [ Info: [10] train-mlogloss:0.37795233825842539 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85209254870812101 [ Info: [2] train-mlogloss:0.67414155403772991 [ Info: [3] train-mlogloss:0.54295411010583239 [ Info: [4] train-mlogloss:0.44392832020918527 [ Info: [5] train-mlogloss:0.36708050693074862 [ Info: [6] train-mlogloss:0.30659253125389418 [ Info: [7] train-mlogloss:0.25804267625013988 [ Info: [8] train-mlogloss:0.21946258234481017 [ Info: [9] train-mlogloss:0.18708838336169720 [ Info: [10] train-mlogloss:0.16111627606054146 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74391969939072922 [ Info: [2] train-mlogloss:0.52955184727907179 [ Info: [3] train-mlogloss:0.39051086902618409 [ Info: [4] train-mlogloss:0.29628119170665740 [ Info: [5] train-mlogloss:0.22936041404803595 [ Info: [6] train-mlogloss:0.18034067663053671 [ Info: [7] train-mlogloss:0.14448922928422689 [ Info: [8] train-mlogloss:0.11796427058676878 [ Info: [9] train-mlogloss:0.09814294632524252 [ Info: [10] train-mlogloss:0.08247979311272502 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97044846167167031 [ Info: [2] train-mlogloss:0.86026118844747546 [ Info: [3] train-mlogloss:0.76653815011183424 [ Info: [4] train-mlogloss:0.68597821046908691 [ Info: [5] train-mlogloss:0.61655587951342261 [ Info: [6] train-mlogloss:0.55598993450403211 [ Info: [7] train-mlogloss:0.50286740536491081 [ Info: [8] train-mlogloss:0.45606419419248900 [ Info: [9] train-mlogloss:0.41467392817139626 [ Info: [10] train-mlogloss:0.37795233825842539 [ Info: [11] train-mlogloss:0.34528242995341618 [ Info: [12] train-mlogloss:0.31592470233639081 [ Info: [13] train-mlogloss:0.28987866590420402 [ Info: [14] train-mlogloss:0.26633166993657748 [ Info: [15] train-mlogloss:0.24540419168770314 [ Info: [16] train-mlogloss:0.22644300907850265 [ Info: [17] train-mlogloss:0.20957709153493245 [ Info: [18] train-mlogloss:0.19367829052110513 [ Info: [19] train-mlogloss:0.17995876582960288 [ Info: [20] train-mlogloss:0.16755533466736475 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85209254870812101 [ Info: [2] train-mlogloss:0.67414155403772991 [ Info: [3] train-mlogloss:0.54295411010583239 [ Info: [4] train-mlogloss:0.44392832020918527 [ Info: [5] train-mlogloss:0.36708050693074862 [ Info: [6] train-mlogloss:0.30659253125389418 [ Info: [7] train-mlogloss:0.25804267625013988 [ Info: [8] train-mlogloss:0.21946258234481017 [ Info: [9] train-mlogloss:0.18708838336169720 [ Info: [10] train-mlogloss:0.16111627606054146 [ Info: [11] train-mlogloss:0.13988524128993352 [ Info: [12] train-mlogloss:0.12245234350363414 [ Info: [13] train-mlogloss:0.10807812611262003 [ Info: [14] train-mlogloss:0.09617777088036140 [ Info: [15] train-mlogloss:0.08579476779947678 [ Info: [16] train-mlogloss:0.07736046432207028 [ Info: [17] train-mlogloss:0.07030276587853829 [ Info: [18] train-mlogloss:0.06422400608037909 [ Info: [19] train-mlogloss:0.05919123074660699 [ Info: [20] train-mlogloss:0.05480971500898401 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74391969939072922 [ Info: [2] train-mlogloss:0.52955184727907179 [ Info: [3] train-mlogloss:0.39051086902618409 [ Info: [4] train-mlogloss:0.29628119170665740 [ Info: [5] train-mlogloss:0.22936041404803595 [ Info: [6] train-mlogloss:0.18034067663053671 [ Info: [7] train-mlogloss:0.14448922928422689 [ Info: [8] train-mlogloss:0.11796427058676878 [ Info: [9] train-mlogloss:0.09814294632524252 [ Info: [10] train-mlogloss:0.08247979311272502 [ Info: [11] train-mlogloss:0.07086049842958649 [ Info: [12] train-mlogloss:0.06174228185166915 [ Info: [13] train-mlogloss:0.05477980955814322 [ Info: [14] train-mlogloss:0.04948024737338225 [ Info: [15] train-mlogloss:0.04501846500982841 [ Info: [16] train-mlogloss:0.04101765921805054 [ Info: [17] train-mlogloss:0.03794657502633830 [ Info: [18] train-mlogloss:0.03499730413313955 [ Info: [19] train-mlogloss:0.03254248965531588 [ Info: [20] train-mlogloss:0.03139157696471860 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97236151049534481 [ Info: [2] train-mlogloss:0.86480532636245089 [ Info: [3] train-mlogloss:0.77323314001162846 [ Info: [4] train-mlogloss:0.69439183771610258 [ Info: [5] train-mlogloss:0.62497639705737429 [ Info: [6] train-mlogloss:0.56442558715740843 [ Info: [7] train-mlogloss:0.51060231849551196 [ Info: [8] train-mlogloss:0.46317101145784062 [ Info: [9] train-mlogloss:0.42121562138199808 [ Info: [10] train-mlogloss:0.38396737997730573 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85591602524121602 [ Info: [2] train-mlogloss:0.68029610266288121 [ Info: [3] train-mlogloss:0.55062675476074219 [ Info: [4] train-mlogloss:0.45066284537315371 [ Info: [5] train-mlogloss:0.37297037765383723 [ Info: [6] train-mlogloss:0.31195452436804771 [ Info: [7] train-mlogloss:0.26330678835511206 [ Info: [8] train-mlogloss:0.22420111075043678 [ Info: [9] train-mlogloss:0.19284623699883621 [ Info: [10] train-mlogloss:0.16730647074679533 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74965017884969709 [ Info: [2] train-mlogloss:0.53832416484753287 [ Info: [3] train-mlogloss:0.39882083162665366 [ Info: [4] train-mlogloss:0.30364120081067086 [ Info: [5] train-mlogloss:0.23631494268774986 [ Info: [6] train-mlogloss:0.18818997157116732 [ Info: [7] train-mlogloss:0.15289382450282574 [ Info: [8] train-mlogloss:0.12624630996336539 [ Info: [9] train-mlogloss:0.10658668198933204 [ Info: [10] train-mlogloss:0.09070351157958309 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97236151049534481 [ Info: [2] train-mlogloss:0.86480532636245089 [ Info: [3] train-mlogloss:0.77323314001162846 [ Info: [4] train-mlogloss:0.69439183771610258 [ Info: [5] train-mlogloss:0.62497639705737429 [ Info: [6] train-mlogloss:0.56442558715740843 [ Info: [7] train-mlogloss:0.51060231849551196 [ Info: [8] train-mlogloss:0.46317101145784062 [ Info: [9] train-mlogloss:0.42121562138199808 [ Info: [10] train-mlogloss:0.38396737997730573 [ Info: [11] train-mlogloss:0.35094066013892494 [ Info: [12] train-mlogloss:0.32146053860584894 [ Info: [13] train-mlogloss:0.29509051591157914 [ Info: [14] train-mlogloss:0.27145637708405651 [ Info: [15] train-mlogloss:0.25023701017101607 [ Info: [16] train-mlogloss:0.23115526003142198 [ Info: [17] train-mlogloss:0.21412497349083423 [ Info: [18] train-mlogloss:0.19876328520476819 [ Info: [19] train-mlogloss:0.18488855262597401 [ Info: [20] train-mlogloss:0.17234129769106707 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85591602524121602 [ Info: [2] train-mlogloss:0.68029610266288121 [ Info: [3] train-mlogloss:0.55062675476074219 [ Info: [4] train-mlogloss:0.45066284537315371 [ Info: [5] train-mlogloss:0.37297037765383723 [ Info: [6] train-mlogloss:0.31195452436804771 [ Info: [7] train-mlogloss:0.26330678835511206 [ Info: [8] train-mlogloss:0.22420111075043678 [ Info: [9] train-mlogloss:0.19284623699883621 [ Info: [10] train-mlogloss:0.16730647074679533 [ Info: [11] train-mlogloss:0.14607734475284814 [ Info: [12] train-mlogloss:0.12888328079134226 [ Info: [13] train-mlogloss:0.11453833325455585 [ Info: [14] train-mlogloss:0.10273646873732407 [ Info: [15] train-mlogloss:0.09235432861993710 [ Info: [16] train-mlogloss:0.08319480267042915 [ Info: [17] train-mlogloss:0.07504694899544120 [ Info: [18] train-mlogloss:0.06832930569847424 [ Info: [19] train-mlogloss:0.06255158986896277 [ Info: [20] train-mlogloss:0.05742745692841709 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74965017884969709 [ Info: [2] train-mlogloss:0.53832416484753287 [ Info: [3] train-mlogloss:0.39882083162665366 [ Info: [4] train-mlogloss:0.30364120081067086 [ Info: [5] train-mlogloss:0.23631494268774986 [ Info: [6] train-mlogloss:0.18818997157116732 [ Info: [7] train-mlogloss:0.15289382450282574 [ Info: [8] train-mlogloss:0.12624630996336539 [ Info: [9] train-mlogloss:0.10658668198933204 [ Info: [10] train-mlogloss:0.09070351157958309 [ Info: [11] train-mlogloss:0.07766839197526375 [ Info: [12] train-mlogloss:0.06766341446588436 [ Info: [13] train-mlogloss:0.05920110009610653 [ Info: [14] train-mlogloss:0.05248417006805539 [ Info: [15] train-mlogloss:0.04777539609931410 [ Info: [16] train-mlogloss:0.04316086892504245 [ Info: [17] train-mlogloss:0.03989025879806529 [ Info: [18] train-mlogloss:0.03718621713730196 [ Info: [19] train-mlogloss:0.03507212595238040 [ Info: [20] train-mlogloss:0.03385302551711599 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96928822000821435 [ Info: [2] train-mlogloss:0.86078089028596882 [ Info: [3] train-mlogloss:0.76844480087359746 [ Info: [4] train-mlogloss:0.68899280925591788 [ Info: [5] train-mlogloss:0.61954725931088128 [ Info: [6] train-mlogloss:0.55932908256848657 [ Info: [7] train-mlogloss:0.50603147844473517 [ Info: [8] train-mlogloss:0.45940263097484907 [ Info: [9] train-mlogloss:0.41774678925673164 [ Info: [10] train-mlogloss:0.38076042508085567 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85000698069731395 [ Info: [2] train-mlogloss:0.67567543933788932 [ Info: [3] train-mlogloss:0.54562055518229802 [ Info: [4] train-mlogloss:0.44724854777256645 [ Info: [5] train-mlogloss:0.36997114246090251 [ Info: [6] train-mlogloss:0.30960007160902026 [ Info: [7] train-mlogloss:0.26082728952169421 [ Info: [8] train-mlogloss:0.22167551654080550 [ Info: [9] train-mlogloss:0.18924930617213248 [ Info: [10] train-mlogloss:0.16299362108111382 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74115428328514099 [ Info: [2] train-mlogloss:0.53199243148167930 [ Info: [3] train-mlogloss:0.39402322148283325 [ Info: [4] train-mlogloss:0.29923300246397655 [ Info: [5] train-mlogloss:0.23265837368865808 [ Info: [6] train-mlogloss:0.18290277446309725 [ Info: [7] train-mlogloss:0.14639067271103462 [ Info: [8] train-mlogloss:0.11946686400721471 [ Info: [9] train-mlogloss:0.09873654066274563 [ Info: [10] train-mlogloss:0.08282258082181215 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96928822000821435 [ Info: [2] train-mlogloss:0.86078089028596882 [ Info: [3] train-mlogloss:0.76844480087359746 [ Info: [4] train-mlogloss:0.68899280925591788 [ Info: [5] train-mlogloss:0.61954725931088128 [ Info: [6] train-mlogloss:0.55932908256848657 [ Info: [7] train-mlogloss:0.50603147844473517 [ Info: [8] train-mlogloss:0.45940263097484907 [ Info: [9] train-mlogloss:0.41774678925673164 [ Info: [10] train-mlogloss:0.38076042508085567 [ Info: [11] train-mlogloss:0.34810653328895569 [ Info: [12] train-mlogloss:0.31865008721748989 [ Info: [13] train-mlogloss:0.29231527509788674 [ Info: [14] train-mlogloss:0.26870095580816267 [ Info: [15] train-mlogloss:0.24766207089026768 [ Info: [16] train-mlogloss:0.22855792964498203 [ Info: [17] train-mlogloss:0.21095109507441520 [ Info: [18] train-mlogloss:0.19510977665583293 [ Info: [19] train-mlogloss:0.18087242903808753 [ Info: [20] train-mlogloss:0.16796836567421755 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85000698069731395 [ Info: [2] train-mlogloss:0.67567543933788932 [ Info: [3] train-mlogloss:0.54562055518229802 [ Info: [4] train-mlogloss:0.44724854777256645 [ Info: [5] train-mlogloss:0.36997114246090251 [ Info: [6] train-mlogloss:0.30960007160902026 [ Info: [7] train-mlogloss:0.26082728952169421 [ Info: [8] train-mlogloss:0.22167551654080550 [ Info: [9] train-mlogloss:0.18924930617213248 [ Info: [10] train-mlogloss:0.16299362108111382 [ Info: [11] train-mlogloss:0.14149054257820051 [ Info: [12] train-mlogloss:0.12414264635493358 [ Info: [13] train-mlogloss:0.10956239967296520 [ Info: [14] train-mlogloss:0.09716725650553902 [ Info: [15] train-mlogloss:0.08668326440577706 [ Info: [16] train-mlogloss:0.07820293859889110 [ Info: [17] train-mlogloss:0.07104801951597134 [ Info: [18] train-mlogloss:0.06505342271799842 [ Info: [19] train-mlogloss:0.06000643180062373 [ Info: [20] train-mlogloss:0.05571428964224955 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74115428328514099 [ Info: [2] train-mlogloss:0.53199243148167930 [ Info: [3] train-mlogloss:0.39402322148283325 [ Info: [4] train-mlogloss:0.29923300246397655 [ Info: [5] train-mlogloss:0.23265837368865808 [ Info: [6] train-mlogloss:0.18290277446309725 [ Info: [7] train-mlogloss:0.14639067271103462 [ Info: [8] train-mlogloss:0.11946686400721471 [ Info: [9] train-mlogloss:0.09873654066274563 [ Info: [10] train-mlogloss:0.08282258082181215 [ Info: [11] train-mlogloss:0.07109017831583818 [ Info: [12] train-mlogloss:0.06213402769838770 [ Info: [13] train-mlogloss:0.05520835492449502 [ Info: [14] train-mlogloss:0.04984052960450450 [ Info: [15] train-mlogloss:0.04479622237849980 [ Info: [16] train-mlogloss:0.04078532446486254 [ Info: [17] train-mlogloss:0.03728081566126396 [ Info: [18] train-mlogloss:0.03487501180109878 [ Info: [19] train-mlogloss:0.03249070287371675 [ Info: [20] train-mlogloss:0.03067546160503601 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96623764038085935 [ Info: [2] train-mlogloss:0.85521393517653144 [ Info: [3] train-mlogloss:0.76077918807665512 [ Info: [4] train-mlogloss:0.67960446675618491 [ Info: [5] train-mlogloss:0.60925572117169702 [ Info: [6] train-mlogloss:0.54789125025272367 [ Info: [7] train-mlogloss:0.49407914107044537 [ Info: [8] train-mlogloss:0.44666638374328616 [ Info: [9] train-mlogloss:0.40509627337257065 [ Info: [10] train-mlogloss:0.36821104586124420 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84413632104794190 [ Info: [2] train-mlogloss:0.66585902671019237 [ Info: [3] train-mlogloss:0.53430792987346654 [ Info: [4] train-mlogloss:0.43426235914230349 [ Info: [5] train-mlogloss:0.35729566315809885 [ Info: [6] train-mlogloss:0.29486198524634044 [ Info: [7] train-mlogloss:0.24593944214284419 [ Info: [8] train-mlogloss:0.20645451471209525 [ Info: [9] train-mlogloss:0.17460463742415111 [ Info: [10] train-mlogloss:0.14877502694725991 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73270757098992667 [ Info: [2] train-mlogloss:0.51924107323090241 [ Info: [3] train-mlogloss:0.38043759390711784 [ Info: [4] train-mlogloss:0.28630925416946412 [ Info: [5] train-mlogloss:0.21792374948660534 [ Info: [6] train-mlogloss:0.16866677229603130 [ Info: [7] train-mlogloss:0.13281922657042741 [ Info: [8] train-mlogloss:0.10680393806348244 [ Info: [9] train-mlogloss:0.08754392812649409 [ Info: [10] train-mlogloss:0.07318307776004077 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96623764038085935 [ Info: [2] train-mlogloss:0.85521393517653144 [ Info: [3] train-mlogloss:0.76077918807665512 [ Info: [4] train-mlogloss:0.67960446675618491 [ Info: [5] train-mlogloss:0.60925572117169702 [ Info: [6] train-mlogloss:0.54789125025272367 [ Info: [7] train-mlogloss:0.49407914107044537 [ Info: [8] train-mlogloss:0.44666638374328616 [ Info: [9] train-mlogloss:0.40509627337257065 [ Info: [10] train-mlogloss:0.36821104586124420 [ Info: [11] train-mlogloss:0.33440148979425433 [ Info: [12] train-mlogloss:0.30431334997216858 [ Info: [13] train-mlogloss:0.27777556329965591 [ Info: [14] train-mlogloss:0.25402414090931413 [ Info: [15] train-mlogloss:0.23258091633518538 [ Info: [16] train-mlogloss:0.21332636537651220 [ Info: [17] train-mlogloss:0.19601325144370396 [ Info: [18] train-mlogloss:0.18042604898413023 [ Info: [19] train-mlogloss:0.16637642669181030 [ Info: [20] train-mlogloss:0.15369879677891732 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84413632104794190 [ Info: [2] train-mlogloss:0.66585902671019237 [ Info: [3] train-mlogloss:0.53430792987346654 [ Info: [4] train-mlogloss:0.43426235914230349 [ Info: [5] train-mlogloss:0.35729566315809885 [ Info: [6] train-mlogloss:0.29486198524634044 [ Info: [7] train-mlogloss:0.24593944214284419 [ Info: [8] train-mlogloss:0.20645451471209525 [ Info: [9] train-mlogloss:0.17460463742415111 [ Info: [10] train-mlogloss:0.14877502694725991 [ Info: [11] train-mlogloss:0.12800429270913202 [ Info: [12] train-mlogloss:0.11105069865783056 [ Info: [13] train-mlogloss:0.09714517357448736 [ Info: [14] train-mlogloss:0.08571286918595433 [ Info: [15] train-mlogloss:0.07509548918654521 [ Info: [16] train-mlogloss:0.06621928292637071 [ Info: [17] train-mlogloss:0.05878650406375528 [ Info: [18] train-mlogloss:0.05267644620810946 [ Info: [19] train-mlogloss:0.04727741326205433 [ Info: [20] train-mlogloss:0.04300854286799828 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73270757098992667 [ Info: [2] train-mlogloss:0.51924107323090241 [ Info: [3] train-mlogloss:0.38043759390711784 [ Info: [4] train-mlogloss:0.28630925416946412 [ Info: [5] train-mlogloss:0.21792374948660534 [ Info: [6] train-mlogloss:0.16866677229603130 [ Info: [7] train-mlogloss:0.13281922657042741 [ Info: [8] train-mlogloss:0.10680393806348244 [ Info: [9] train-mlogloss:0.08754392812649409 [ Info: [10] train-mlogloss:0.07318307776004077 [ Info: [11] train-mlogloss:0.06082860237608353 [ Info: [12] train-mlogloss:0.05155442473478615 [ Info: [13] train-mlogloss:0.04428179707999031 [ Info: [14] train-mlogloss:0.03756030793301761 [ Info: [15] train-mlogloss:0.03235830996806423 [ Info: [16] train-mlogloss:0.02895866828039289 [ Info: [17] train-mlogloss:0.02633465998806059 [ Info: [18] train-mlogloss:0.02403726937870184 [ Info: [19] train-mlogloss:0.02233322972897440 [ Info: [20] train-mlogloss:0.02169226870561640 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96748082041740413 [ Info: [2] train-mlogloss:0.85737070639928181 [ Info: [3] train-mlogloss:0.76372242818276093 [ Info: [4] train-mlogloss:0.68315339833498001 [ Info: [5] train-mlogloss:0.61324565261602404 [ Info: [6] train-mlogloss:0.55221853057543435 [ Info: [7] train-mlogloss:0.49896644949913027 [ Info: [8] train-mlogloss:0.45232639114061990 [ Info: [9] train-mlogloss:0.41074146752556168 [ Info: [10] train-mlogloss:0.37380343427260715 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84650223255157475 [ Info: [2] train-mlogloss:0.66977323442697523 [ Info: [3] train-mlogloss:0.53910726656516395 [ Info: [4] train-mlogloss:0.44010963415106136 [ Info: [5] train-mlogloss:0.36305676748355231 [ Info: [6] train-mlogloss:0.30231260682145755 [ Info: [7] train-mlogloss:0.25380709966023762 [ Info: [8] train-mlogloss:0.21511453452209631 [ Info: [9] train-mlogloss:0.18360094899932544 [ Info: [10] train-mlogloss:0.15804893535872300 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73607121706008916 [ Info: [2] train-mlogloss:0.52412821749846139 [ Info: [3] train-mlogloss:0.38755649179220197 [ Info: [4] train-mlogloss:0.29306036258737245 [ Info: [5] train-mlogloss:0.22597838081419469 [ Info: [6] train-mlogloss:0.17755772396922112 [ Info: [7] train-mlogloss:0.14215344972908497 [ Info: [8] train-mlogloss:0.11508924985925356 [ Info: [9] train-mlogloss:0.09439749239633481 [ Info: [10] train-mlogloss:0.07860914592941602 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96748082041740413 [ Info: [2] train-mlogloss:0.85737070639928181 [ Info: [3] train-mlogloss:0.76372242818276093 [ Info: [4] train-mlogloss:0.68315339833498001 [ Info: [5] train-mlogloss:0.61324565261602404 [ Info: [6] train-mlogloss:0.55221853057543435 [ Info: [7] train-mlogloss:0.49896644949913027 [ Info: [8] train-mlogloss:0.45232639114061990 [ Info: [9] train-mlogloss:0.41074146752556168 [ Info: [10] train-mlogloss:0.37380343427260715 [ Info: [11] train-mlogloss:0.34091445580124857 [ Info: [12] train-mlogloss:0.31155878628293671 [ Info: [13] train-mlogloss:0.28529974371194838 [ Info: [14] train-mlogloss:0.26176664133866628 [ Info: [15] train-mlogloss:0.24062020207444826 [ Info: [16] train-mlogloss:0.22164121319850286 [ Info: [17] train-mlogloss:0.20449989947179953 [ Info: [18] train-mlogloss:0.18929999073346457 [ Info: [19] train-mlogloss:0.17539649978280067 [ Info: [20] train-mlogloss:0.16297533797721067 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84650223255157475 [ Info: [2] train-mlogloss:0.66977323442697523 [ Info: [3] train-mlogloss:0.53910726656516395 [ Info: [4] train-mlogloss:0.44010963415106136 [ Info: [5] train-mlogloss:0.36305676748355231 [ Info: [6] train-mlogloss:0.30231260682145755 [ Info: [7] train-mlogloss:0.25380709966023762 [ Info: [8] train-mlogloss:0.21511453452209631 [ Info: [9] train-mlogloss:0.18360094899932544 [ Info: [10] train-mlogloss:0.15804893535872300 [ Info: [11] train-mlogloss:0.13638640431066354 [ Info: [12] train-mlogloss:0.11875038910657168 [ Info: [13] train-mlogloss:0.10427096318453551 [ Info: [14] train-mlogloss:0.09200416704018911 [ Info: [15] train-mlogloss:0.08153477193166812 [ Info: [16] train-mlogloss:0.07278551993270715 [ Info: [17] train-mlogloss:0.06560093689089021 [ Info: [18] train-mlogloss:0.05941545935347677 [ Info: [19] train-mlogloss:0.05447370054510733 [ Info: [20] train-mlogloss:0.05018589872245987 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73607121706008916 [ Info: [2] train-mlogloss:0.52412821749846139 [ Info: [3] train-mlogloss:0.38755649179220197 [ Info: [4] train-mlogloss:0.29306036258737245 [ Info: [5] train-mlogloss:0.22597838081419469 [ Info: [6] train-mlogloss:0.17755772396922112 [ Info: [7] train-mlogloss:0.14215344972908497 [ Info: [8] train-mlogloss:0.11508924985925356 [ Info: [9] train-mlogloss:0.09439749239633481 [ Info: [10] train-mlogloss:0.07860914592941602 [ Info: [11] train-mlogloss:0.06687739165499806 [ Info: [12] train-mlogloss:0.05751719606729845 [ Info: [13] train-mlogloss:0.05073458859696985 [ Info: [14] train-mlogloss:0.04527132480094830 [ Info: [15] train-mlogloss:0.04044246062015493 [ Info: [16] train-mlogloss:0.03697994113899768 [ Info: [17] train-mlogloss:0.03409726192088177 [ Info: [18] train-mlogloss:0.03190291766077280 [ Info: [19] train-mlogloss:0.02981716349410514 [ Info: [20] train-mlogloss:0.02898266674407447 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96802820066610973 [ Info: [2] train-mlogloss:0.85791043738524120 [ Info: [3] train-mlogloss:0.76413537462552383 [ Info: [4] train-mlogloss:0.68374677151441576 [ Info: [5] train-mlogloss:0.61398622393608093 [ Info: [6] train-mlogloss:0.55345377723375955 [ Info: [7] train-mlogloss:0.50026642580827074 [ Info: [8] train-mlogloss:0.45370886599024135 [ Info: [9] train-mlogloss:0.41211618557572366 [ Info: [10] train-mlogloss:0.37516874745488166 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84755997757116952 [ Info: [2] train-mlogloss:0.67015360246102018 [ Info: [3] train-mlogloss:0.53971385061740873 [ Info: [4] train-mlogloss:0.44080103288094202 [ Info: [5] train-mlogloss:0.36436081777016321 [ Info: [6] train-mlogloss:0.30347874959309895 [ Info: [7] train-mlogloss:0.25488679309686024 [ Info: [8] train-mlogloss:0.21593288791676363 [ Info: [9] train-mlogloss:0.18438732437789440 [ Info: [10] train-mlogloss:0.15815912925948700 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73760499109824496 [ Info: [2] train-mlogloss:0.52615421464045842 [ Info: [3] train-mlogloss:0.38869107340772946 [ Info: [4] train-mlogloss:0.29481353660424553 [ Info: [5] train-mlogloss:0.22759976883729299 [ Info: [6] train-mlogloss:0.17915657212336858 [ Info: [7] train-mlogloss:0.14095217920839787 [ Info: [8] train-mlogloss:0.11338605793813865 [ Info: [9] train-mlogloss:0.09311952609568834 [ Info: [10] train-mlogloss:0.07754220794886350 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96802820066610973 [ Info: [2] train-mlogloss:0.85791043738524120 [ Info: [3] train-mlogloss:0.76413537462552383 [ Info: [4] train-mlogloss:0.68374677151441576 [ Info: [5] train-mlogloss:0.61398622393608093 [ Info: [6] train-mlogloss:0.55345377723375955 [ Info: [7] train-mlogloss:0.50026642580827074 [ Info: [8] train-mlogloss:0.45370886599024135 [ Info: [9] train-mlogloss:0.41211618557572366 [ Info: [10] train-mlogloss:0.37516874745488166 [ Info: [11] train-mlogloss:0.34225685621301333 [ Info: [12] train-mlogloss:0.31286644265055658 [ Info: [13] train-mlogloss:0.28656355962157248 [ Info: [14] train-mlogloss:0.26297788036366304 [ Info: [15] train-mlogloss:0.24179084698359171 [ Info: [16] train-mlogloss:0.22273199955622355 [ Info: [17] train-mlogloss:0.20562017088135084 [ Info: [18] train-mlogloss:0.19054154828190803 [ Info: [19] train-mlogloss:0.17631698722640674 [ Info: [20] train-mlogloss:0.16341449655592441 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84755997757116952 [ Info: [2] train-mlogloss:0.67015360246102018 [ Info: [3] train-mlogloss:0.53971385061740873 [ Info: [4] train-mlogloss:0.44080103288094202 [ Info: [5] train-mlogloss:0.36436081777016321 [ Info: [6] train-mlogloss:0.30347874959309895 [ Info: [7] train-mlogloss:0.25488679309686024 [ Info: [8] train-mlogloss:0.21593288791676363 [ Info: [9] train-mlogloss:0.18438732437789440 [ Info: [10] train-mlogloss:0.15815912925948700 [ Info: [11] train-mlogloss:0.13588811041166385 [ Info: [12] train-mlogloss:0.11782302235563596 [ Info: [13] train-mlogloss:0.10308883214990298 [ Info: [14] train-mlogloss:0.09069380539779862 [ Info: [15] train-mlogloss:0.08036936176940798 [ Info: [16] train-mlogloss:0.07181801119198401 [ Info: [17] train-mlogloss:0.06477424505477150 [ Info: [18] train-mlogloss:0.05881397503738602 [ Info: [19] train-mlogloss:0.05403416523089011 [ Info: [20] train-mlogloss:0.04964113216847181 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73760499109824496 [ Info: [2] train-mlogloss:0.52615421464045842 [ Info: [3] train-mlogloss:0.38869107340772946 [ Info: [4] train-mlogloss:0.29481353660424553 [ Info: [5] train-mlogloss:0.22759976883729299 [ Info: [6] train-mlogloss:0.17915657212336858 [ Info: [7] train-mlogloss:0.14095217920839787 [ Info: [8] train-mlogloss:0.11338605793813865 [ Info: [9] train-mlogloss:0.09311952609568834 [ Info: [10] train-mlogloss:0.07754220794886350 [ Info: [11] train-mlogloss:0.06582255152364572 [ Info: [12] train-mlogloss:0.05687872505125900 [ Info: [13] train-mlogloss:0.05046575941766302 [ Info: [14] train-mlogloss:0.04484759874952336 [ Info: [15] train-mlogloss:0.04050325723364949 [ Info: [16] train-mlogloss:0.03675344556880494 [ Info: [17] train-mlogloss:0.03356105087635418 [ Info: [18] train-mlogloss:0.03109780789042512 [ Info: [19] train-mlogloss:0.02902008609380573 [ Info: [20] train-mlogloss:0.02786389553608994 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97004122237364454 [ Info: [2] train-mlogloss:0.86210669030745823 [ Info: [3] train-mlogloss:0.77022417883078254 [ Info: [4] train-mlogloss:0.69118552009264633 [ Info: [5] train-mlogloss:0.62127224057912822 [ Info: [6] train-mlogloss:0.56023854364951453 [ Info: [7] train-mlogloss:0.50666571383674941 [ Info: [8] train-mlogloss:0.45942864964405694 [ Info: [9] train-mlogloss:0.41761898199717201 [ Info: [10] train-mlogloss:0.38049221361676849 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85143254051605866 [ Info: [2] train-mlogloss:0.67792762418588004 [ Info: [3] train-mlogloss:0.54703325927257540 [ Info: [4] train-mlogloss:0.44729705279072124 [ Info: [5] train-mlogloss:0.36974424620469409 [ Info: [6] train-mlogloss:0.30851861486832299 [ Info: [7] train-mlogloss:0.26005115347603958 [ Info: [8] train-mlogloss:0.22091938207546871 [ Info: [9] train-mlogloss:0.18941021909316380 [ Info: [10] train-mlogloss:0.16363127473741770 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74316988041003540 [ Info: [2] train-mlogloss:0.53123704095681512 [ Info: [3] train-mlogloss:0.39301102807124455 [ Info: [4] train-mlogloss:0.29807468007008237 [ Info: [5] train-mlogloss:0.23110592675705752 [ Info: [6] train-mlogloss:0.18256918390591939 [ Info: [7] train-mlogloss:0.14702260339011750 [ Info: [8] train-mlogloss:0.12042475317915281 [ Info: [9] train-mlogloss:0.09878806710864106 [ Info: [10] train-mlogloss:0.08271996596207222 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97004122237364454 [ Info: [2] train-mlogloss:0.86210669030745823 [ Info: [3] train-mlogloss:0.77022417883078254 [ Info: [4] train-mlogloss:0.69118552009264633 [ Info: [5] train-mlogloss:0.62127224057912822 [ Info: [6] train-mlogloss:0.56023854364951453 [ Info: [7] train-mlogloss:0.50666571383674941 [ Info: [8] train-mlogloss:0.45942864964405694 [ Info: [9] train-mlogloss:0.41761898199717201 [ Info: [10] train-mlogloss:0.38049221361676849 [ Info: [11] train-mlogloss:0.34741287256280579 [ Info: [12] train-mlogloss:0.31788219337662060 [ Info: [13] train-mlogloss:0.29163349022467933 [ Info: [14] train-mlogloss:0.26807519855598611 [ Info: [15] train-mlogloss:0.24689143660167853 [ Info: [16] train-mlogloss:0.22781538255512715 [ Info: [17] train-mlogloss:0.21059615810712179 [ Info: [18] train-mlogloss:0.19517453648149968 [ Info: [19] train-mlogloss:0.18121541254222392 [ Info: [20] train-mlogloss:0.16856300632158916 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85143254051605866 [ Info: [2] train-mlogloss:0.67792762418588004 [ Info: [3] train-mlogloss:0.54703325927257540 [ Info: [4] train-mlogloss:0.44729705279072124 [ Info: [5] train-mlogloss:0.36974424620469409 [ Info: [6] train-mlogloss:0.30851861486832299 [ Info: [7] train-mlogloss:0.26005115347603958 [ Info: [8] train-mlogloss:0.22091938207546871 [ Info: [9] train-mlogloss:0.18941021909316380 [ Info: [10] train-mlogloss:0.16363127473741770 [ Info: [11] train-mlogloss:0.14241968269149463 [ Info: [12] train-mlogloss:0.12435393432776133 [ Info: [13] train-mlogloss:0.10956530831754208 [ Info: [14] train-mlogloss:0.09736170507967472 [ Info: [15] train-mlogloss:0.08722958341240883 [ Info: [16] train-mlogloss:0.07851771100734671 [ Info: [17] train-mlogloss:0.07161698093016942 [ Info: [18] train-mlogloss:0.06515195217604439 [ Info: [19] train-mlogloss:0.05993448082978527 [ Info: [20] train-mlogloss:0.05505179505174359 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74316988041003540 [ Info: [2] train-mlogloss:0.53123704095681512 [ Info: [3] train-mlogloss:0.39301102807124455 [ Info: [4] train-mlogloss:0.29807468007008237 [ Info: [5] train-mlogloss:0.23110592675705752 [ Info: [6] train-mlogloss:0.18256918390591939 [ Info: [7] train-mlogloss:0.14702260339011750 [ Info: [8] train-mlogloss:0.12042475317915281 [ Info: [9] train-mlogloss:0.09878806710864106 [ Info: [10] train-mlogloss:0.08271996596207222 [ Info: [11] train-mlogloss:0.07068845030541221 [ Info: [12] train-mlogloss:0.06169708284238974 [ Info: [13] train-mlogloss:0.05373783063453932 [ Info: [14] train-mlogloss:0.04741776532803973 [ Info: [15] train-mlogloss:0.04272597790695727 [ Info: [16] train-mlogloss:0.03921865189137558 [ Info: [17] train-mlogloss:0.03553912178613246 [ Info: [18] train-mlogloss:0.03314536068743715 [ Info: [19] train-mlogloss:0.03105310740259786 [ Info: [20] train-mlogloss:0.02990498677439367 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96926355317786883 [ Info: [2] train-mlogloss:0.86079001735757898 [ Info: [3] train-mlogloss:0.76851826552991509 [ Info: [4] train-mlogloss:0.68913874405401720 [ Info: [5] train-mlogloss:0.62029619790889601 [ Info: [6] train-mlogloss:0.56018583509657116 [ Info: [7] train-mlogloss:0.50741448623162733 [ Info: [8] train-mlogloss:0.46089044897644610 [ Info: [9] train-mlogloss:0.41971808340814376 [ Info: [10] train-mlogloss:0.38256126178635491 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85001058490188031 [ Info: [2] train-mlogloss:0.67583194176355998 [ Info: [3] train-mlogloss:0.54699281233328356 [ Info: [4] train-mlogloss:0.44881407684750030 [ Info: [5] train-mlogloss:0.37148633687584487 [ Info: [6] train-mlogloss:0.31109064530443264 [ Info: [7] train-mlogloss:0.26212182707256743 [ Info: [8] train-mlogloss:0.22272729465255031 [ Info: [9] train-mlogloss:0.19033886679896603 [ Info: [10] train-mlogloss:0.16358457594006151 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74124272355326903 [ Info: [2] train-mlogloss:0.53236660339214181 [ Info: [3] train-mlogloss:0.39614491308176958 [ Info: [4] train-mlogloss:0.30117015595789309 [ Info: [5] train-mlogloss:0.23352586836726577 [ Info: [6] train-mlogloss:0.18323042194048564 [ Info: [7] train-mlogloss:0.14663289123111301 [ Info: [8] train-mlogloss:0.11890040398747832 [ Info: [9] train-mlogloss:0.09790000694769400 [ Info: [10] train-mlogloss:0.08206577496948066 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96926355317786883 [ Info: [2] train-mlogloss:0.86079001735757898 [ Info: [3] train-mlogloss:0.76851826552991509 [ Info: [4] train-mlogloss:0.68913874405401720 [ Info: [5] train-mlogloss:0.62029619790889601 [ Info: [6] train-mlogloss:0.56018583509657116 [ Info: [7] train-mlogloss:0.50741448623162733 [ Info: [8] train-mlogloss:0.46089044897644610 [ Info: [9] train-mlogloss:0.41971808340814376 [ Info: [10] train-mlogloss:0.38256126178635491 [ Info: [11] train-mlogloss:0.34952857648884811 [ Info: [12] train-mlogloss:0.31993945395504986 [ Info: [13] train-mlogloss:0.29343910261436745 [ Info: [14] train-mlogloss:0.26972887880272334 [ Info: [15] train-mlogloss:0.24833594637888448 [ Info: [16] train-mlogloss:0.22906795265497984 [ Info: [17] train-mlogloss:0.21176031066311729 [ Info: [18] train-mlogloss:0.19613826606008741 [ Info: [19] train-mlogloss:0.18179242633007192 [ Info: [20] train-mlogloss:0.16886447276230213 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85001058490188031 [ Info: [2] train-mlogloss:0.67583194176355998 [ Info: [3] train-mlogloss:0.54699281233328356 [ Info: [4] train-mlogloss:0.44881407684750030 [ Info: [5] train-mlogloss:0.37148633687584487 [ Info: [6] train-mlogloss:0.31109064530443264 [ Info: [7] train-mlogloss:0.26212182707256743 [ Info: [8] train-mlogloss:0.22272729465255031 [ Info: [9] train-mlogloss:0.19033886679896603 [ Info: [10] train-mlogloss:0.16358457594006151 [ Info: [11] train-mlogloss:0.14198963338578188 [ Info: [12] train-mlogloss:0.12392541705458253 [ Info: [13] train-mlogloss:0.10857903990480634 [ Info: [14] train-mlogloss:0.09583056111026693 [ Info: [15] train-mlogloss:0.08522864756760774 [ Info: [16] train-mlogloss:0.07637034177228257 [ Info: [17] train-mlogloss:0.06918702627773639 [ Info: [18] train-mlogloss:0.06318142836292585 [ Info: [19] train-mlogloss:0.05732475548154778 [ Info: [20] train-mlogloss:0.05283719266730326 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74124272355326903 [ Info: [2] train-mlogloss:0.53236660339214181 [ Info: [3] train-mlogloss:0.39614491308176958 [ Info: [4] train-mlogloss:0.30117015595789309 [ Info: [5] train-mlogloss:0.23352586836726577 [ Info: [6] train-mlogloss:0.18323042194048564 [ Info: [7] train-mlogloss:0.14663289123111301 [ Info: [8] train-mlogloss:0.11890040398747832 [ Info: [9] train-mlogloss:0.09790000694769400 [ Info: [10] train-mlogloss:0.08206577496948066 [ Info: [11] train-mlogloss:0.07032518784205119 [ Info: [12] train-mlogloss:0.06135215553696509 [ Info: [13] train-mlogloss:0.05425611283216211 [ Info: [14] train-mlogloss:0.04730967326020753 [ Info: [15] train-mlogloss:0.04266573350048727 [ Info: [16] train-mlogloss:0.03883655761816987 [ Info: [17] train-mlogloss:0.03594219855688236 [ Info: [18] train-mlogloss:0.03321159666887036 [ Info: [19] train-mlogloss:0.03094055065540252 [ Info: [20] train-mlogloss:0.02937811217443259 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96692725508301347 [ Info: [2] train-mlogloss:0.85659519787187932 [ Info: [3] train-mlogloss:0.76280089396017570 [ Info: [4] train-mlogloss:0.68219537205166292 [ Info: [5] train-mlogloss:0.61233968602286448 [ Info: [6] train-mlogloss:0.55139393718154339 [ Info: [7] train-mlogloss:0.49793125876673944 [ Info: [8] train-mlogloss:0.45066672298643323 [ Info: [9] train-mlogloss:0.40883822794313784 [ Info: [10] train-mlogloss:0.37169889454488403 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84551761945088699 [ Info: [2] train-mlogloss:0.66851157347361245 [ Info: [3] train-mlogloss:0.53791214404282750 [ Info: [4] train-mlogloss:0.43852001494831511 [ Info: [5] train-mlogloss:0.36098930217601632 [ Info: [6] train-mlogloss:0.29983023846590962 [ Info: [7] train-mlogloss:0.25176358730704695 [ Info: [8] train-mlogloss:0.21257214866302632 [ Info: [9] train-mlogloss:0.18099589965961599 [ Info: [10] train-mlogloss:0.15529696455708256 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73477951332374858 [ Info: [2] train-mlogloss:0.52294769309185174 [ Info: [3] train-mlogloss:0.38505279510109514 [ Info: [4] train-mlogloss:0.28999903886406508 [ Info: [5] train-mlogloss:0.22379815556384899 [ Info: [6] train-mlogloss:0.17510105879218490 [ Info: [7] train-mlogloss:0.13953065507941775 [ Info: [8] train-mlogloss:0.11355114479859670 [ Info: [9] train-mlogloss:0.09408333596807938 [ Info: [10] train-mlogloss:0.07874316057121312 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96692725508301347 [ Info: [2] train-mlogloss:0.85659519787187932 [ Info: [3] train-mlogloss:0.76280089396017570 [ Info: [4] train-mlogloss:0.68219537205166292 [ Info: [5] train-mlogloss:0.61233968602286448 [ Info: [6] train-mlogloss:0.55139393718154339 [ Info: [7] train-mlogloss:0.49793125876673944 [ Info: [8] train-mlogloss:0.45066672298643323 [ Info: [9] train-mlogloss:0.40883822794313784 [ Info: [10] train-mlogloss:0.37169889454488403 [ Info: [11] train-mlogloss:0.33862952325079176 [ Info: [12] train-mlogloss:0.30921238086841724 [ Info: [13] train-mlogloss:0.28313645201700705 [ Info: [14] train-mlogloss:0.25950952139165667 [ Info: [15] train-mlogloss:0.23856960005230374 [ Info: [16] train-mlogloss:0.21946440791642224 [ Info: [17] train-mlogloss:0.20231822640807540 [ Info: [18] train-mlogloss:0.18685454063945348 [ Info: [19] train-mlogloss:0.17289267756320811 [ Info: [20] train-mlogloss:0.16027229875326157 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84551761945088699 [ Info: [2] train-mlogloss:0.66851157347361245 [ Info: [3] train-mlogloss:0.53791214404282750 [ Info: [4] train-mlogloss:0.43852001494831511 [ Info: [5] train-mlogloss:0.36098930217601632 [ Info: [6] train-mlogloss:0.29983023846590962 [ Info: [7] train-mlogloss:0.25176358730704695 [ Info: [8] train-mlogloss:0.21257214866302632 [ Info: [9] train-mlogloss:0.18099589965961599 [ Info: [10] train-mlogloss:0.15529696455708256 [ Info: [11] train-mlogloss:0.13427984736583851 [ Info: [12] train-mlogloss:0.11703410683958619 [ Info: [13] train-mlogloss:0.10294203405027036 [ Info: [14] train-mlogloss:0.09125678889729359 [ Info: [15] train-mlogloss:0.08117341233624352 [ Info: [16] train-mlogloss:0.07260748868187268 [ Info: [17] train-mlogloss:0.06550583585544868 [ Info: [18] train-mlogloss:0.05958807530502478 [ Info: [19] train-mlogloss:0.05441794763836596 [ Info: [20] train-mlogloss:0.04998555202726965 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73477951332374858 [ Info: [2] train-mlogloss:0.52294769309185174 [ Info: [3] train-mlogloss:0.38505279510109514 [ Info: [4] train-mlogloss:0.28999903886406508 [ Info: [5] train-mlogloss:0.22379815556384899 [ Info: [6] train-mlogloss:0.17510105879218490 [ Info: [7] train-mlogloss:0.13953065507941775 [ Info: [8] train-mlogloss:0.11355114479859670 [ Info: [9] train-mlogloss:0.09408333596807938 [ Info: [10] train-mlogloss:0.07874316057121312 [ Info: [11] train-mlogloss:0.06677882345738234 [ Info: [12] train-mlogloss:0.05781377889215946 [ Info: [13] train-mlogloss:0.05059476828685514 [ Info: [14] train-mlogloss:0.04480648414680252 [ Info: [15] train-mlogloss:0.04051157193327391 [ Info: [16] train-mlogloss:0.03702580681139672 [ Info: [17] train-mlogloss:0.03449471589453795 [ Info: [18] train-mlogloss:0.03227060955983621 [ Info: [19] train-mlogloss:0.03044387926520021 [ Info: [20] train-mlogloss:0.02911903089326289 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96926306177068644 [ Info: [2] train-mlogloss:0.86078966149577385 [ Info: [3] train-mlogloss:0.76851834323671131 [ Info: [4] train-mlogloss:0.68914038693463364 [ Info: [5] train-mlogloss:0.62029920242450853 [ Info: [6] train-mlogloss:0.56018940298645581 [ Info: [7] train-mlogloss:0.50740406424910933 [ Info: [8] train-mlogloss:0.46085115980218960 [ Info: [9] train-mlogloss:0.41961824231677586 [ Info: [10] train-mlogloss:0.38246599789018987 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85000977648629084 [ Info: [2] train-mlogloss:0.67583218194820260 [ Info: [3] train-mlogloss:0.54699631002214222 [ Info: [4] train-mlogloss:0.44881994878804243 [ Info: [5] train-mlogloss:0.37235229059501929 [ Info: [6] train-mlogloss:0.31099646864113983 [ Info: [7] train-mlogloss:0.26179588690952016 [ Info: [8] train-mlogloss:0.22228207212907297 [ Info: [9] train-mlogloss:0.18942233202634035 [ Info: [10] train-mlogloss:0.16263913705393121 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74124190145068702 [ Info: [2] train-mlogloss:0.53237111612602517 [ Info: [3] train-mlogloss:0.39615096560230961 [ Info: [4] train-mlogloss:0.30097006471068771 [ Info: [5] train-mlogloss:0.23211332537509777 [ Info: [6] train-mlogloss:0.18231277498934004 [ Info: [7] train-mlogloss:0.14516540136602191 [ Info: [8] train-mlogloss:0.11749018640429885 [ Info: [9] train-mlogloss:0.09679759641488393 [ Info: [10] train-mlogloss:0.08112926085789998 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96926306177068644 [ Info: [2] train-mlogloss:0.86078966149577385 [ Info: [3] train-mlogloss:0.76851834323671131 [ Info: [4] train-mlogloss:0.68914038693463364 [ Info: [5] train-mlogloss:0.62029920242450853 [ Info: [6] train-mlogloss:0.56018940298645581 [ Info: [7] train-mlogloss:0.50740406424910933 [ Info: [8] train-mlogloss:0.46085115980218960 [ Info: [9] train-mlogloss:0.41961824231677586 [ Info: [10] train-mlogloss:0.38246599789018987 [ Info: [11] train-mlogloss:0.34938672030413592 [ Info: [12] train-mlogloss:0.31984086014606333 [ Info: [13] train-mlogloss:0.29337716323358043 [ Info: [14] train-mlogloss:0.26963572159961419 [ Info: [15] train-mlogloss:0.24814864794413249 [ Info: [16] train-mlogloss:0.22847335669729446 [ Info: [17] train-mlogloss:0.21074285330595793 [ Info: [18] train-mlogloss:0.19474304417769114 [ Info: [19] train-mlogloss:0.18028647071785397 [ Info: [20] train-mlogloss:0.16720875424367410 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85000977648629084 [ Info: [2] train-mlogloss:0.67583218194820260 [ Info: [3] train-mlogloss:0.54699631002214222 [ Info: [4] train-mlogloss:0.44881994878804243 [ Info: [5] train-mlogloss:0.37235229059501929 [ Info: [6] train-mlogloss:0.31099646864113983 [ Info: [7] train-mlogloss:0.26179588690952016 [ Info: [8] train-mlogloss:0.22228207212907297 [ Info: [9] train-mlogloss:0.18942233202634035 [ Info: [10] train-mlogloss:0.16263913705393121 [ Info: [11] train-mlogloss:0.14045584003130596 [ Info: [12] train-mlogloss:0.12209823236421302 [ Info: [13] train-mlogloss:0.10696765189921414 [ Info: [14] train-mlogloss:0.09444455860389603 [ Info: [15] train-mlogloss:0.08399864192362184 [ Info: [16] train-mlogloss:0.07558117315725044 [ Info: [17] train-mlogloss:0.06846817795325208 [ Info: [18] train-mlogloss:0.06249182948635684 [ Info: [19] train-mlogloss:0.05701779481713418 [ Info: [20] train-mlogloss:0.05249853308002154 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74124190145068702 [ Info: [2] train-mlogloss:0.53237111612602517 [ Info: [3] train-mlogloss:0.39615096560230961 [ Info: [4] train-mlogloss:0.30097006471068771 [ Info: [5] train-mlogloss:0.23211332537509777 [ Info: [6] train-mlogloss:0.18231277498934004 [ Info: [7] train-mlogloss:0.14516540136602191 [ Info: [8] train-mlogloss:0.11749018640429885 [ Info: [9] train-mlogloss:0.09679759641488393 [ Info: [10] train-mlogloss:0.08112926085789998 [ Info: [11] train-mlogloss:0.06960491880222604 [ Info: [12] train-mlogloss:0.06063841891785463 [ Info: [13] train-mlogloss:0.05284873542410356 [ Info: [14] train-mlogloss:0.04616683772592633 [ Info: [15] train-mlogloss:0.04135701476975723 [ Info: [16] train-mlogloss:0.03797680873561789 [ Info: [17] train-mlogloss:0.03517064314887480 [ Info: [18] train-mlogloss:0.03268126498355910 [ Info: [19] train-mlogloss:0.03064582671418234 [ Info: [20] train-mlogloss:0.02903432127916150 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96875828681168730 [ Info: [2] train-mlogloss:0.85929890650290031 [ Info: [3] train-mlogloss:0.76639026006062827 [ Info: [4] train-mlogloss:0.68649969630771213 [ Info: [5] train-mlogloss:0.61721339314072221 [ Info: [6] train-mlogloss:0.55674962820830165 [ Info: [7] train-mlogloss:0.50396974108837267 [ Info: [8] train-mlogloss:0.45768991046481661 [ Info: [9] train-mlogloss:0.41644700522776001 [ Info: [10] train-mlogloss:0.37980081174108715 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84900945778246284 [ Info: [2] train-mlogloss:0.67313049766752453 [ Info: [3] train-mlogloss:0.54335242598145095 [ Info: [4] train-mlogloss:0.44504216975635952 [ Info: [5] train-mlogloss:0.36905241983908194 [ Info: [6] train-mlogloss:0.30854633008992233 [ Info: [7] train-mlogloss:0.25952963034311932 [ Info: [8] train-mlogloss:0.21993802631342851 [ Info: [9] train-mlogloss:0.18715123158914071 [ Info: [10] train-mlogloss:0.16080312408782818 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73974968636477434 [ Info: [2] train-mlogloss:0.52853596563692451 [ Info: [3] train-mlogloss:0.39281995230250888 [ Info: [4] train-mlogloss:0.29884496022153784 [ Info: [5] train-mlogloss:0.23066381116708121 [ Info: [6] train-mlogloss:0.18044141365422142 [ Info: [7] train-mlogloss:0.14408052480883068 [ Info: [8] train-mlogloss:0.11765550275643667 [ Info: [9] train-mlogloss:0.09795348760154513 [ Info: [10] train-mlogloss:0.08215466668760335 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96875828681168730 [ Info: [2] train-mlogloss:0.85929890650290031 [ Info: [3] train-mlogloss:0.76639026006062827 [ Info: [4] train-mlogloss:0.68649969630771213 [ Info: [5] train-mlogloss:0.61721339314072221 [ Info: [6] train-mlogloss:0.55674962820830165 [ Info: [7] train-mlogloss:0.50396974108837267 [ Info: [8] train-mlogloss:0.45768991046481661 [ Info: [9] train-mlogloss:0.41644700522776001 [ Info: [10] train-mlogloss:0.37980081174108715 [ Info: [11] train-mlogloss:0.34715354420520639 [ Info: [12] train-mlogloss:0.31754556033346387 [ Info: [13] train-mlogloss:0.29106678454964247 [ Info: [14] train-mlogloss:0.26732555473292313 [ Info: [15] train-mlogloss:0.24601041332439141 [ Info: [16] train-mlogloss:0.22684258564754770 [ Info: [17] train-mlogloss:0.20919440267262635 [ Info: [18] train-mlogloss:0.19326691704767721 [ Info: [19] train-mlogloss:0.17887399086245784 [ Info: [20] train-mlogloss:0.16585209148901481 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84900945778246284 [ Info: [2] train-mlogloss:0.67313049766752453 [ Info: [3] train-mlogloss:0.54335242598145095 [ Info: [4] train-mlogloss:0.44504216975635952 [ Info: [5] train-mlogloss:0.36905241983908194 [ Info: [6] train-mlogloss:0.30854633008992233 [ Info: [7] train-mlogloss:0.25952963034311932 [ Info: [8] train-mlogloss:0.21993802631342851 [ Info: [9] train-mlogloss:0.18715123158914071 [ Info: [10] train-mlogloss:0.16080312408782818 [ Info: [11] train-mlogloss:0.13893922832277086 [ Info: [12] train-mlogloss:0.12144438828583116 [ Info: [13] train-mlogloss:0.10667235100710834 [ Info: [14] train-mlogloss:0.09476434547040198 [ Info: [15] train-mlogloss:0.08437190331794597 [ Info: [16] train-mlogloss:0.07569634583261278 [ Info: [17] train-mlogloss:0.06839052896808695 [ Info: [18] train-mlogloss:0.06273890623339901 [ Info: [19] train-mlogloss:0.05710564048753845 [ Info: [20] train-mlogloss:0.05242691081431177 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73974968636477434 [ Info: [2] train-mlogloss:0.52853596563692451 [ Info: [3] train-mlogloss:0.39281995230250888 [ Info: [4] train-mlogloss:0.29884496022153784 [ Info: [5] train-mlogloss:0.23066381116708121 [ Info: [6] train-mlogloss:0.18044141365422142 [ Info: [7] train-mlogloss:0.14408052480883068 [ Info: [8] train-mlogloss:0.11765550275643667 [ Info: [9] train-mlogloss:0.09795348760154513 [ Info: [10] train-mlogloss:0.08215466668760335 [ Info: [11] train-mlogloss:0.07013957958530496 [ Info: [12] train-mlogloss:0.05964430533349514 [ Info: [13] train-mlogloss:0.05214135891033544 [ Info: [14] train-mlogloss:0.04593786313026040 [ Info: [15] train-mlogloss:0.04103271692163414 [ Info: [16] train-mlogloss:0.03788066883054045 [ Info: [17] train-mlogloss:0.03518054644680686 [ Info: [18] train-mlogloss:0.03273729539165894 [ Info: [19] train-mlogloss:0.03094328866098766 [ Info: [20] train-mlogloss:0.02953675415504862 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97011229153032652 [ Info: [2] train-mlogloss:0.86237275070614283 [ Info: [3] train-mlogloss:0.77069864979496705 [ Info: [4] train-mlogloss:0.69186869947998608 [ Info: [5] train-mlogloss:0.62350126769807601 [ Info: [6] train-mlogloss:0.56302995196095218 [ Info: [7] train-mlogloss:0.50993350368958934 [ Info: [8] train-mlogloss:0.46312628719541760 [ Info: [9] train-mlogloss:0.42170074692478887 [ Info: [10] train-mlogloss:0.38432416628908228 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85166426764594183 [ Info: [2] train-mlogloss:0.67870280742645261 [ Info: [3] train-mlogloss:0.55075797239939372 [ Info: [4] train-mlogloss:0.45188413063685101 [ Info: [5] train-mlogloss:0.37499000452182912 [ Info: [6] train-mlogloss:0.31317171079141121 [ Info: [7] train-mlogloss:0.26375959537647387 [ Info: [8] train-mlogloss:0.22409750885433621 [ Info: [9] train-mlogloss:0.19111087951395248 [ Info: [10] train-mlogloss:0.16421976232970203 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74365670460241817 [ Info: [2] train-mlogloss:0.53636570109261406 [ Info: [3] train-mlogloss:0.39902546295413266 [ Info: [4] train-mlogloss:0.30344510255036533 [ Info: [5] train-mlogloss:0.23535267489927786 [ Info: [6] train-mlogloss:0.18499652202482578 [ Info: [7] train-mlogloss:0.14801252351866828 [ Info: [8] train-mlogloss:0.12051911160901740 [ Info: [9] train-mlogloss:0.10011211749580172 [ Info: [10] train-mlogloss:0.08414191559508995 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.97011229153032652 [ Info: [2] train-mlogloss:0.86237275070614283 [ Info: [3] train-mlogloss:0.77069864979496705 [ Info: [4] train-mlogloss:0.69186869947998608 [ Info: [5] train-mlogloss:0.62350126769807601 [ Info: [6] train-mlogloss:0.56302995196095218 [ Info: [7] train-mlogloss:0.50993350368958934 [ Info: [8] train-mlogloss:0.46312628719541760 [ Info: [9] train-mlogloss:0.42170074692478887 [ Info: [10] train-mlogloss:0.38432416628908228 [ Info: [11] train-mlogloss:0.35107821689711677 [ Info: [12] train-mlogloss:0.32130657986358357 [ Info: [13] train-mlogloss:0.29464857578277587 [ Info: [14] train-mlogloss:0.27080224498554512 [ Info: [15] train-mlogloss:0.24929160155631877 [ Info: [16] train-mlogloss:0.22992171921111920 [ Info: [17] train-mlogloss:0.21209600634045070 [ Info: [18] train-mlogloss:0.19600925511784023 [ Info: [19] train-mlogloss:0.18147315647866991 [ Info: [20] train-mlogloss:0.16832239208398042 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.85166426764594183 [ Info: [2] train-mlogloss:0.67870280742645261 [ Info: [3] train-mlogloss:0.55075797239939372 [ Info: [4] train-mlogloss:0.45188413063685101 [ Info: [5] train-mlogloss:0.37499000452182912 [ Info: [6] train-mlogloss:0.31317171079141121 [ Info: [7] train-mlogloss:0.26375959537647387 [ Info: [8] train-mlogloss:0.22409750885433621 [ Info: [9] train-mlogloss:0.19111087951395248 [ Info: [10] train-mlogloss:0.16421976232970203 [ Info: [11] train-mlogloss:0.14218536521549577 [ Info: [12] train-mlogloss:0.12404700004392200 [ Info: [13] train-mlogloss:0.10905105714444761 [ Info: [14] train-mlogloss:0.09667738275947395 [ Info: [15] train-mlogloss:0.08616855293512345 [ Info: [16] train-mlogloss:0.07741007495809485 [ Info: [17] train-mlogloss:0.06994709573962070 [ Info: [18] train-mlogloss:0.06345912191878866 [ Info: [19] train-mlogloss:0.05784884881642130 [ Info: [20] train-mlogloss:0.05293734951151742 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.74365670460241817 [ Info: [2] train-mlogloss:0.53636570109261406 [ Info: [3] train-mlogloss:0.39902546295413266 [ Info: [4] train-mlogloss:0.30344510255036533 [ Info: [5] train-mlogloss:0.23535267489927786 [ Info: [6] train-mlogloss:0.18499652202482578 [ Info: [7] train-mlogloss:0.14801252351866828 [ Info: [8] train-mlogloss:0.12051911160901740 [ Info: [9] train-mlogloss:0.10011211749580172 [ Info: [10] train-mlogloss:0.08414191559508995 [ Info: [11] train-mlogloss:0.07193364487202079 [ Info: [12] train-mlogloss:0.06255353763699531 [ Info: [13] train-mlogloss:0.05467934506358924 [ Info: [14] train-mlogloss:0.04841812855943486 [ Info: [15] train-mlogloss:0.04337156903412607 [ Info: [16] train-mlogloss:0.03980432297620509 [ Info: [17] train-mlogloss:0.03701085313050835 [ Info: [18] train-mlogloss:0.03422248303476307 [ Info: [19] train-mlogloss:0.03199769238492957 [ Info: [20] train-mlogloss:0.03038808907968579 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96858481742717606 [ Info: [2] train-mlogloss:0.85963092821615716 [ Info: [3] train-mlogloss:0.76638182887324580 [ Info: [4] train-mlogloss:0.68670082754558992 [ Info: [5] train-mlogloss:0.61763970454533890 [ Info: [6] train-mlogloss:0.55689622781894821 [ Info: [7] train-mlogloss:0.50401173035303748 [ Info: [8] train-mlogloss:0.45695732898182340 [ Info: [9] train-mlogloss:0.41568864252832199 [ Info: [10] train-mlogloss:0.37866325047281052 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84873724072067824 [ Info: [2] train-mlogloss:0.67272049276917067 [ Info: [3] train-mlogloss:0.54353323865819858 [ Info: [4] train-mlogloss:0.44519917501343620 [ Info: [5] train-mlogloss:0.36792812214957343 [ Info: [6] train-mlogloss:0.30700720438250789 [ Info: [7] train-mlogloss:0.25792888204256692 [ Info: [8] train-mlogloss:0.21829534956702479 [ Info: [9] train-mlogloss:0.18625443908903333 [ Info: [10] train-mlogloss:0.16001550113713300 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73945905190927008 [ Info: [2] train-mlogloss:0.52848133268179720 [ Info: [3] train-mlogloss:0.39195889013784901 [ Info: [4] train-mlogloss:0.29724722901980083 [ Info: [5] train-mlogloss:0.22960687489421280 [ Info: [6] train-mlogloss:0.18041468483430367 [ Info: [7] train-mlogloss:0.14444514038386169 [ Info: [8] train-mlogloss:0.11679617536288721 [ Info: [9] train-mlogloss:0.09515588609156785 [ Info: [10] train-mlogloss:0.07882978571233926 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96858481742717606 [ Info: [2] train-mlogloss:0.85963092821615716 [ Info: [3] train-mlogloss:0.76638182887324580 [ Info: [4] train-mlogloss:0.68670082754558992 [ Info: [5] train-mlogloss:0.61763970454533890 [ Info: [6] train-mlogloss:0.55689622781894821 [ Info: [7] train-mlogloss:0.50401173035303748 [ Info: [8] train-mlogloss:0.45695732898182340 [ Info: [9] train-mlogloss:0.41568864252832199 [ Info: [10] train-mlogloss:0.37866325047281052 [ Info: [11] train-mlogloss:0.34571324454413521 [ Info: [12] train-mlogloss:0.31629142959912621 [ Info: [13] train-mlogloss:0.28989380498727163 [ Info: [14] train-mlogloss:0.26606225128527039 [ Info: [15] train-mlogloss:0.24491246883515957 [ Info: [16] train-mlogloss:0.22558492896733462 [ Info: [17] train-mlogloss:0.20818638591854660 [ Info: [18] train-mlogloss:0.19232569778407060 [ Info: [19] train-mlogloss:0.17817221317026349 [ Info: [20] train-mlogloss:0.16526164142069993 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84873724072067824 [ Info: [2] train-mlogloss:0.67272049276917067 [ Info: [3] train-mlogloss:0.54353323865819858 [ Info: [4] train-mlogloss:0.44519917501343620 [ Info: [5] train-mlogloss:0.36792812214957343 [ Info: [6] train-mlogloss:0.30700720438250789 [ Info: [7] train-mlogloss:0.25792888204256692 [ Info: [8] train-mlogloss:0.21829534956702479 [ Info: [9] train-mlogloss:0.18625443908903333 [ Info: [10] train-mlogloss:0.16001550113713300 [ Info: [11] train-mlogloss:0.13808829618824853 [ Info: [12] train-mlogloss:0.12050879437614370 [ Info: [13] train-mlogloss:0.10559885518418419 [ Info: [14] train-mlogloss:0.09316976509160466 [ Info: [15] train-mlogloss:0.08281869237069731 [ Info: [16] train-mlogloss:0.07348032775852416 [ Info: [17] train-mlogloss:0.06628993007319944 [ Info: [18] train-mlogloss:0.05989676905726945 [ Info: [19] train-mlogloss:0.05470570869467876 [ Info: [20] train-mlogloss:0.05032091027608624 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73945905190927008 [ Info: [2] train-mlogloss:0.52848133268179720 [ Info: [3] train-mlogloss:0.39195889013784901 [ Info: [4] train-mlogloss:0.29724722901980083 [ Info: [5] train-mlogloss:0.22960687489421280 [ Info: [6] train-mlogloss:0.18041468483430367 [ Info: [7] train-mlogloss:0.14444514038386169 [ Info: [8] train-mlogloss:0.11679617536288721 [ Info: [9] train-mlogloss:0.09515588609156785 [ Info: [10] train-mlogloss:0.07882978571233926 [ Info: [11] train-mlogloss:0.06674109208914969 [ Info: [12] train-mlogloss:0.05742648921355054 [ Info: [13] train-mlogloss:0.05020713922050264 [ Info: [14] train-mlogloss:0.04406661376081131 [ Info: [15] train-mlogloss:0.03936308151869862 [ Info: [16] train-mlogloss:0.03599414416347389 [ Info: [17] train-mlogloss:0.03286167686736143 [ Info: [18] train-mlogloss:0.03001064068327347 [ Info: [19] train-mlogloss:0.02783916188679911 [ Info: [20] train-mlogloss:0.02654437855644911 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96604449837296102 [ Info: [2] train-mlogloss:0.85505476969259753 [ Info: [3] train-mlogloss:0.76154180147029737 [ Info: [4] train-mlogloss:0.68122895823584662 [ Info: [5] train-mlogloss:0.61167702586562545 [ Info: [6] train-mlogloss:0.55112717769764086 [ Info: [7] train-mlogloss:0.49797006315655179 [ Info: [8] train-mlogloss:0.45152307638415584 [ Info: [9] train-mlogloss:0.41049241622289023 [ Info: [10] train-mlogloss:0.37322783624684369 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84389184757515234 [ Info: [2] train-mlogloss:0.66746113609384605 [ Info: [3] train-mlogloss:0.53766358163621686 [ Info: [4] train-mlogloss:0.43887196668872125 [ Info: [5] train-mlogloss:0.36129788116172507 [ Info: [6] train-mlogloss:0.30163863102595012 [ Info: [7] train-mlogloss:0.25313592210963920 [ Info: [8] train-mlogloss:0.21415821258668546 [ Info: [9] train-mlogloss:0.18303773822607816 [ Info: [10] train-mlogloss:0.15778709937024998 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73256089245831524 [ Info: [2] train-mlogloss:0.52211370600594420 [ Info: [3] train-mlogloss:0.38606096506118776 [ Info: [4] train-mlogloss:0.29310496317015755 [ Info: [5] train-mlogloss:0.22593217988808950 [ Info: [6] train-mlogloss:0.17754170309614253 [ Info: [7] train-mlogloss:0.14266740757006185 [ Info: [8] train-mlogloss:0.11683878788241633 [ Info: [9] train-mlogloss:0.09746080289284388 [ Info: [10] train-mlogloss:0.08291958311089763 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96604449837296102 [ Info: [2] train-mlogloss:0.85505476969259753 [ Info: [3] train-mlogloss:0.76154180147029737 [ Info: [4] train-mlogloss:0.68122895823584662 [ Info: [5] train-mlogloss:0.61167702586562545 [ Info: [6] train-mlogloss:0.55112717769764086 [ Info: [7] train-mlogloss:0.49797006315655179 [ Info: [8] train-mlogloss:0.45152307638415584 [ Info: [9] train-mlogloss:0.41049241622289023 [ Info: [10] train-mlogloss:0.37322783624684369 [ Info: [11] train-mlogloss:0.34015610814094543 [ Info: [12] train-mlogloss:0.31131913374971459 [ Info: [13] train-mlogloss:0.28498789712234779 [ Info: [14] train-mlogloss:0.26136092035858721 [ Info: [15] train-mlogloss:0.24026484577744095 [ Info: [16] train-mlogloss:0.22133758266766865 [ Info: [17] train-mlogloss:0.20433865421348149 [ Info: [18] train-mlogloss:0.18911822482391641 [ Info: [19] train-mlogloss:0.17540078218336458 [ Info: [20] train-mlogloss:0.16301891284960288 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84389184757515234 [ Info: [2] train-mlogloss:0.66746113609384605 [ Info: [3] train-mlogloss:0.53766358163621686 [ Info: [4] train-mlogloss:0.43887196668872125 [ Info: [5] train-mlogloss:0.36129788116172507 [ Info: [6] train-mlogloss:0.30163863102595012 [ Info: [7] train-mlogloss:0.25313592210963920 [ Info: [8] train-mlogloss:0.21415821258668546 [ Info: [9] train-mlogloss:0.18303773822607816 [ Info: [10] train-mlogloss:0.15778709937024998 [ Info: [11] train-mlogloss:0.13715405988472479 [ Info: [12] train-mlogloss:0.12008456466374574 [ Info: [13] train-mlogloss:0.10610058677417261 [ Info: [14] train-mlogloss:0.09456544937910857 [ Info: [15] train-mlogloss:0.08495186547990198 [ Info: [16] train-mlogloss:0.07608132097456190 [ Info: [17] train-mlogloss:0.06857203874323103 [ Info: [18] train-mlogloss:0.06214541318239989 [ Info: [19] train-mlogloss:0.05678297241252882 [ Info: [20] train-mlogloss:0.05215264344932857 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73256089245831524 [ Info: [2] train-mlogloss:0.52211370600594420 [ Info: [3] train-mlogloss:0.38606096506118776 [ Info: [4] train-mlogloss:0.29310496317015755 [ Info: [5] train-mlogloss:0.22593217988808950 [ Info: [6] train-mlogloss:0.17754170309614253 [ Info: [7] train-mlogloss:0.14266740757006185 [ Info: [8] train-mlogloss:0.11683878788241633 [ Info: [9] train-mlogloss:0.09746080289284388 [ Info: [10] train-mlogloss:0.08291958311089763 [ Info: [11] train-mlogloss:0.07062403407913667 [ Info: [12] train-mlogloss:0.06094277779813166 [ Info: [13] train-mlogloss:0.05345397307365029 [ Info: [14] train-mlogloss:0.04818823839779254 [ Info: [15] train-mlogloss:0.04283052456599695 [ Info: [16] train-mlogloss:0.03832505694418042 [ Info: [17] train-mlogloss:0.03555390973471933 [ Info: [18] train-mlogloss:0.03323959787548692 [ Info: [19] train-mlogloss:0.03149652440031921 [ Info: [20] train-mlogloss:0.03011314491223958 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96607205823615749 [ Info: [2] train-mlogloss:0.85503694746229386 [ Info: [3] train-mlogloss:0.76059020492765639 [ Info: [4] train-mlogloss:0.67948794364929199 [ Info: [5] train-mlogloss:0.60917760531107590 [ Info: [6] train-mlogloss:0.54817490445242989 [ Info: [7] train-mlogloss:0.49432679458900736 [ Info: [8] train-mlogloss:0.44746606062959743 [ Info: [9] train-mlogloss:0.40573318777260958 [ Info: [10] train-mlogloss:0.36870232688056098 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84390409610889572 [ Info: [2] train-mlogloss:0.66616255530604607 [ Info: [3] train-mlogloss:0.53489151133431334 [ Info: [4] train-mlogloss:0.43551809456613327 [ Info: [5] train-mlogloss:0.35829248538723696 [ Info: [6] train-mlogloss:0.29729933385495788 [ Info: [7] train-mlogloss:0.24916308577413912 [ Info: [8] train-mlogloss:0.21019405766769692 [ Info: [9] train-mlogloss:0.17879964322955519 [ Info: [10] train-mlogloss:0.15355174519397594 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73251510063807168 [ Info: [2] train-mlogloss:0.51970721902670680 [ Info: [3] train-mlogloss:0.38269281122419568 [ Info: [4] train-mlogloss:0.28791704884281866 [ Info: [5] train-mlogloss:0.22098233114790033 [ Info: [6] train-mlogloss:0.17290589312712351 [ Info: [7] train-mlogloss:0.13741316370390080 [ Info: [8] train-mlogloss:0.11008791338514398 [ Info: [9] train-mlogloss:0.08985078845311094 [ Info: [10] train-mlogloss:0.07427205374395406 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96607205823615749 [ Info: [2] train-mlogloss:0.85503694746229386 [ Info: [3] train-mlogloss:0.76059020492765639 [ Info: [4] train-mlogloss:0.67948794364929199 [ Info: [5] train-mlogloss:0.60917760531107590 [ Info: [6] train-mlogloss:0.54817490445242989 [ Info: [7] train-mlogloss:0.49432679458900736 [ Info: [8] train-mlogloss:0.44746606062959743 [ Info: [9] train-mlogloss:0.40573318777260958 [ Info: [10] train-mlogloss:0.36870232688056098 [ Info: [11] train-mlogloss:0.33575133217705622 [ Info: [12] train-mlogloss:0.30636472437116835 [ Info: [13] train-mlogloss:0.28008417641675032 [ Info: [14] train-mlogloss:0.25654577899862219 [ Info: [15] train-mlogloss:0.23541354084456409 [ Info: [16] train-mlogloss:0.21642155040193486 [ Info: [17] train-mlogloss:0.19934851295418210 [ Info: [18] train-mlogloss:0.18410186425403313 [ Info: [19] train-mlogloss:0.17019735144244300 [ Info: [20] train-mlogloss:0.15774489839871725 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84390409610889572 [ Info: [2] train-mlogloss:0.66616255530604607 [ Info: [3] train-mlogloss:0.53489151133431334 [ Info: [4] train-mlogloss:0.43551809456613327 [ Info: [5] train-mlogloss:0.35829248538723696 [ Info: [6] train-mlogloss:0.29729933385495788 [ Info: [7] train-mlogloss:0.24916308577413912 [ Info: [8] train-mlogloss:0.21019405766769692 [ Info: [9] train-mlogloss:0.17879964322955519 [ Info: [10] train-mlogloss:0.15355174519397594 [ Info: [11] train-mlogloss:0.13273521981857442 [ Info: [12] train-mlogloss:0.11468743008595926 [ Info: [13] train-mlogloss:0.10020835383070839 [ Info: [14] train-mlogloss:0.08795222819403366 [ Info: [15] train-mlogloss:0.07788308077940234 [ Info: [16] train-mlogloss:0.06920311622045658 [ Info: [17] train-mlogloss:0.06192995254640226 [ Info: [18] train-mlogloss:0.05593700544149787 [ Info: [19] train-mlogloss:0.05090736153501051 [ Info: [20] train-mlogloss:0.04668929404406636 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73251510063807168 [ Info: [2] train-mlogloss:0.51970721902670680 [ Info: [3] train-mlogloss:0.38269281122419568 [ Info: [4] train-mlogloss:0.28791704884281866 [ Info: [5] train-mlogloss:0.22098233114790033 [ Info: [6] train-mlogloss:0.17290589312712351 [ Info: [7] train-mlogloss:0.13741316370390080 [ Info: [8] train-mlogloss:0.11008791338514398 [ Info: [9] train-mlogloss:0.08985078845311094 [ Info: [10] train-mlogloss:0.07427205374395406 [ Info: [11] train-mlogloss:0.06239906828160639 [ Info: [12] train-mlogloss:0.05331377944460622 [ Info: [13] train-mlogloss:0.04635956756494664 [ Info: [14] train-mlogloss:0.04087419722367216 [ Info: [15] train-mlogloss:0.03683981111756077 [ Info: [16] train-mlogloss:0.03334204825676150 [ Info: [17] train-mlogloss:0.03096740037478782 [ Info: [18] train-mlogloss:0.02866496304395022 [ Info: [19] train-mlogloss:0.02661716397161837 [ Info: [20] train-mlogloss:0.02504417536159357 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96674630730240430 [ Info: [2] train-mlogloss:0.85579189238724884 [ Info: [3] train-mlogloss:0.76137815139911791 [ Info: [4] train-mlogloss:0.68052925533718533 [ Info: [5] train-mlogloss:0.61042803790834210 [ Info: [6] train-mlogloss:0.54953249030643037 [ Info: [7] train-mlogloss:0.49610237192224571 [ Info: [8] train-mlogloss:0.44902024114573441 [ Info: [9] train-mlogloss:0.40758426299801581 [ Info: [10] train-mlogloss:0.37054259710841708 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84521832024609600 [ Info: [2] train-mlogloss:0.66673783726162383 [ Info: [3] train-mlogloss:0.53575475657427751 [ Info: [4] train-mlogloss:0.43639582218947232 [ Info: [5] train-mlogloss:0.35978824871557730 [ Info: [6] train-mlogloss:0.29929319730511417 [ Info: [7] train-mlogloss:0.25068225341814537 [ Info: [8] train-mlogloss:0.21170639318448525 [ Info: [9] train-mlogloss:0.17911746214937280 [ Info: [10] train-mlogloss:0.15320473975605434 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73443582411165587 [ Info: [2] train-mlogloss:0.52032314583107275 [ Info: [3] train-mlogloss:0.38367969459957546 [ Info: [4] train-mlogloss:0.28992781219659031 [ Info: [5] train-mlogloss:0.22303682311817452 [ Info: [6] train-mlogloss:0.17322846838721523 [ Info: [7] train-mlogloss:0.13780772178261369 [ Info: [8] train-mlogloss:0.11160545437424271 [ Info: [9] train-mlogloss:0.09142774967131791 [ Info: [10] train-mlogloss:0.07548832415982529 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96674630730240430 [ Info: [2] train-mlogloss:0.85579189238724884 [ Info: [3] train-mlogloss:0.76137815139911791 [ Info: [4] train-mlogloss:0.68052925533718533 [ Info: [5] train-mlogloss:0.61042803790834210 [ Info: [6] train-mlogloss:0.54953249030643037 [ Info: [7] train-mlogloss:0.49610237192224571 [ Info: [8] train-mlogloss:0.44902024114573441 [ Info: [9] train-mlogloss:0.40758426299801581 [ Info: [10] train-mlogloss:0.37054259710841708 [ Info: [11] train-mlogloss:0.33756591434831973 [ Info: [12] train-mlogloss:0.30813601877954272 [ Info: [13] train-mlogloss:0.28181312062122205 [ Info: [14] train-mlogloss:0.25822355449199674 [ Info: [15] train-mlogloss:0.23710966430328512 [ Info: [16] train-mlogloss:0.21812415763183876 [ Info: [17] train-mlogloss:0.20102803022773177 [ Info: [18] train-mlogloss:0.18530899540141776 [ Info: [19] train-mlogloss:0.17116934436338918 [ Info: [20] train-mlogloss:0.15838069706051439 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84521832024609600 [ Info: [2] train-mlogloss:0.66673783726162383 [ Info: [3] train-mlogloss:0.53575475657427751 [ Info: [4] train-mlogloss:0.43639582218947232 [ Info: [5] train-mlogloss:0.35978824871557730 [ Info: [6] train-mlogloss:0.29929319730511417 [ Info: [7] train-mlogloss:0.25068225341814537 [ Info: [8] train-mlogloss:0.21170639318448525 [ Info: [9] train-mlogloss:0.17911746214937280 [ Info: [10] train-mlogloss:0.15320473975605434 [ Info: [11] train-mlogloss:0.13203660702263867 [ Info: [12] train-mlogloss:0.11392651437609284 [ Info: [13] train-mlogloss:0.09935381097926034 [ Info: [14] train-mlogloss:0.08686547897480153 [ Info: [15] train-mlogloss:0.07672343761832626 [ Info: [16] train-mlogloss:0.06825485163264805 [ Info: [17] train-mlogloss:0.06115331183429117 [ Info: [18] train-mlogloss:0.05532123762424345 [ Info: [19] train-mlogloss:0.05029992262522379 [ Info: [20] train-mlogloss:0.04609442380843339 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73443582411165587 [ Info: [2] train-mlogloss:0.52032314583107275 [ Info: [3] train-mlogloss:0.38367969459957546 [ Info: [4] train-mlogloss:0.28992781219659031 [ Info: [5] train-mlogloss:0.22303682311817452 [ Info: [6] train-mlogloss:0.17322846838721523 [ Info: [7] train-mlogloss:0.13780772178261369 [ Info: [8] train-mlogloss:0.11160545437424271 [ Info: [9] train-mlogloss:0.09142774967131791 [ Info: [10] train-mlogloss:0.07548832415982529 [ Info: [11] train-mlogloss:0.06366407145504598 [ Info: [12] train-mlogloss:0.05455109441169986 [ Info: [13] train-mlogloss:0.04760128069255087 [ Info: [14] train-mlogloss:0.04245766500631968 [ Info: [15] train-mlogloss:0.03841512108014689 [ Info: [16] train-mlogloss:0.03485016781422827 [ Info: [17] train-mlogloss:0.03197115031243474 [ Info: [18] train-mlogloss:0.02963334822820293 [ Info: [19] train-mlogloss:0.02780297031557118 [ Info: [20] train-mlogloss:0.02679849323575144 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96877196718145298 [ Info: [2] train-mlogloss:0.85931102655552050 [ Info: [3] train-mlogloss:0.76640140833678072 [ Info: [4] train-mlogloss:0.68651056907795094 [ Info: [5] train-mlogloss:0.61722415288289390 [ Info: [6] train-mlogloss:0.55676045329482471 [ Info: [7] train-mlogloss:0.50406774348682826 [ Info: [8] train-mlogloss:0.45754883488019310 [ Info: [9] train-mlogloss:0.41639336744944255 [ Info: [10] train-mlogloss:0.37984585629569162 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84903466613204392 [ Info: [2] train-mlogloss:0.67315011024475102 [ Info: [3] train-mlogloss:0.54336885964428938 [ Info: [4] train-mlogloss:0.44523295031653509 [ Info: [5] train-mlogloss:0.36884907793115684 [ Info: [6] train-mlogloss:0.30863443524749190 [ Info: [7] train-mlogloss:0.26039175556765665 [ Info: [8] train-mlogloss:0.22085733788984793 [ Info: [9] train-mlogloss:0.18855104954154403 [ Info: [10] train-mlogloss:0.16201111254868683 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73978406058417423 [ Info: [2] train-mlogloss:0.52856011611443976 [ Info: [3] train-mlogloss:0.39315239809177538 [ Info: [4] train-mlogloss:0.29942968289057414 [ Info: [5] train-mlogloss:0.23301916276967083 [ Info: [6] train-mlogloss:0.18444092505508000 [ Info: [7] train-mlogloss:0.14805399096674390 [ Info: [8] train-mlogloss:0.12102569534822746 [ Info: [9] train-mlogloss:0.10091392144008919 [ Info: [10] train-mlogloss:0.08457092976680508 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.96877196718145298 [ Info: [2] train-mlogloss:0.85931102655552050 [ Info: [3] train-mlogloss:0.76640140833678072 [ Info: [4] train-mlogloss:0.68651056907795094 [ Info: [5] train-mlogloss:0.61722415288289390 [ Info: [6] train-mlogloss:0.55676045329482471 [ Info: [7] train-mlogloss:0.50406774348682826 [ Info: [8] train-mlogloss:0.45754883488019310 [ Info: [9] train-mlogloss:0.41639336744944255 [ Info: [10] train-mlogloss:0.37984585629569162 [ Info: [11] train-mlogloss:0.34757876109193875 [ Info: [12] train-mlogloss:0.31852135856946312 [ Info: [13] train-mlogloss:0.29193826538545115 [ Info: [14] train-mlogloss:0.26810541726924753 [ Info: [15] train-mlogloss:0.24670052749139290 [ Info: [16] train-mlogloss:0.22753993040985532 [ Info: [17] train-mlogloss:0.21018432985853266 [ Info: [18] train-mlogloss:0.19449305103884804 [ Info: [19] train-mlogloss:0.18025028473801083 [ Info: [20] train-mlogloss:0.16737351450655197 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.84903466613204392 [ Info: [2] train-mlogloss:0.67315011024475102 [ Info: [3] train-mlogloss:0.54336885964428938 [ Info: [4] train-mlogloss:0.44523295031653509 [ Info: [5] train-mlogloss:0.36884907793115684 [ Info: [6] train-mlogloss:0.30863443524749190 [ Info: [7] train-mlogloss:0.26039175556765665 [ Info: [8] train-mlogloss:0.22085733788984793 [ Info: [9] train-mlogloss:0.18855104954154403 [ Info: [10] train-mlogloss:0.16201111254868683 [ Info: [11] train-mlogloss:0.14045631686846416 [ Info: [12] train-mlogloss:0.12313220230517564 [ Info: [13] train-mlogloss:0.10775584390869847 [ Info: [14] train-mlogloss:0.09503375090382717 [ Info: [15] train-mlogloss:0.08446432948112488 [ Info: [16] train-mlogloss:0.07564661450408124 [ Info: [17] train-mlogloss:0.06825855589575237 [ Info: [18] train-mlogloss:0.06247485525630139 [ Info: [19] train-mlogloss:0.05683085908768354 [ Info: [20] train-mlogloss:0.05197557784892894 [ Info: Training rounds complete. [ Info: XGBoost: starting training. [ Info: [1] train-mlogloss:0.73978406058417423 [ Info: [2] train-mlogloss:0.52856011611443976 [ Info: [3] train-mlogloss:0.39315239809177538 [ Info: [4] train-mlogloss:0.29942968289057414 [ Info: [5] train-mlogloss:0.23301916276967083 [ Info: [6] train-mlogloss:0.18444092505508000 [ Info: [7] train-mlogloss:0.14805399096674390 [ Info: [8] train-mlogloss:0.12102569534822746 [ Info: [9] train-mlogloss:0.10091392144008919 [ Info: [10] train-mlogloss:0.08457092976680508 [ Info: [11] train-mlogloss:0.07338822823431757 [ Info: [12] train-mlogloss:0.06205104801941801 [ Info: [13] train-mlogloss:0.05428690839972761 [ Info: [14] train-mlogloss:0.04696131311357021 [ Info: [15] train-mlogloss:0.04150725865253696 [ Info: [16] train-mlogloss:0.03822395526976497 [ Info: [17] train-mlogloss:0.03559223589383893 [ Info: [18] train-mlogloss:0.03340533120488679 [ Info: [19] train-mlogloss:0.03154071772264110 [ Info: [20] train-mlogloss:0.02988090498579873 [ Info: Training rounds complete. [ Info: For silent loading, specify `verbosity=0`. import MLJXGBoostInterface ✔ ====================================================================================== Information request received. A stacktrace will print followed by a 1.0 second profile. --trace-compile is enabled during profile collection. ====================================================================================== cmd: /opt/julia/bin/julia 1198 running 1 of 1 signal (10): User defined signal 1 subtype_tuple_tail at /source/src/subtype.c:1797:39 [inlined] subtype_tuple at /source/src/subtype.c:1897:15 [inlined] subtype at /source/src/subtype.c:2136:20 exists_subtype at /source/src/subtype.c:2367:13 [inlined] forall_exists_subtype at /source/src/subtype.c:2396:15 ijl_subtype_env at /source/src/subtype.c:2888:19 [inlined] ijl_subtype_env at /source/src/subtype.c:2852:18 jl_type_intersection_env_s at /source/src/subtype.c:5282:9 jl_typemap_intersection_node_visitor at /source/src/typemap.c:549:23 jl_typemap_intersection_visitor at /source/src/typemap.c:814:16 jl_typemap_intersection_memory_visitor at /source/src/typemap.c:506:26 jl_typemap_intersection_visitor at /source/src/typemap.c:804:26 jl_typemap_intersection_visitor at /source/src/typemap.c:730:34 ml_matches at /source/src/gf.c:5017:10 ml_matches at /source/src/gf.c:1668:9 [inlined] cache_method at /source/src/gf.c:1708:16 jl_mt_assoc_by_type at /source/src/gf.c:1979:18 jl_lookup_generic_ at /source/src/gf.c:4334:17 [inlined] ijl_apply_generic at /source/src/gf.c:4360:35 widen_all_consts! at ./../usr/share/julia/Compiler/src/optimize.jl:313:0 (pc: 41) ir_to_codeinf! at ./../usr/share/julia/Compiler/src/optimize.jl:305:0 [inlined] ir_to_codeinf! at ./../usr/share/julia/Compiler/src/optimize.jl:296:0 [inlined] finish! at ./../usr/share/julia/Compiler/src/typeinfer.jl:153:0 (pc: 298) finish_nocycle at ./../usr/share/julia/Compiler/src/typeinfer.jl:285:0 (pc: 61) jfptr_finish_nocycle_1.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4138:23 [inlined] ijl_apply_generic at /source/src/gf.c:4364:12 typeinf at ./../usr/share/julia/Compiler/src/abstractinterpretation.jl:4952:0 (pc: 251) typeinf_ext at ./../usr/share/julia/Compiler/src/typeinfer.jl:1537:0 (pc: 150) typeinf_ext_toplevel at ./../usr/share/julia/Compiler/src/typeinfer.jl:1741:0 [inlined] typeinf_ext_toplevel at ./../usr/share/julia/Compiler/src/typeinfer.jl:1750:0 (pc: 12) jfptr_typeinf_ext_toplevel_3.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4138:23 [inlined] ijl_apply_generic at /source/src/gf.c:4364:12 jl_apply at /source/src/julia.h:2388:12 [inlined] jl_type_infer at /source/src/gf.c:463:35 jl_compile_method_internal at /source/src/gf.c:3665:24 _jl_invoke at /source/src/gf.c:4130:16 [inlined] ijl_apply_generic at /source/src/gf.c:4364:12 evaluate! at /home/pkgeval/.julia/packages/MLJBase/krfwA/src/resampling/evaluate.jl:889:0 (pc: 315) unknown function (ip: 0x74c45e420b6d) at (unknown file) _jl_invoke at /source/src/gf.c:4138:23 [inlined] ijl_apply_generic at /source/src/gf.c:4364:12 evaluate! at /home/pkgeval/.julia/packages/MLJBase/krfwA/src/resampling/evaluate.jl:937:0 (pc: 47) #evaluate!#277 at /home/pkgeval/.julia/packages/MLJBase/krfwA/src/resampling/evaluate.jl:479:0 (pc: 135) unknown function (ip: 0x74c45e41a4c0) at (unknown file) _jl_invoke at /source/src/gf.c:4138:23 [inlined] ijl_apply_generic at /source/src/gf.c:4364:12 evaluate! at /home/pkgeval/.julia/packages/MLJBase/krfwA/src/resampling/evaluate.jl:406:0 (pc: 35) unknown function (ip: 0x74c45e419e84) at (unknown file) _jl_invoke at /source/src/gf.c:4138:23 [inlined] ijl_apply_generic at /source/src/gf.c:4364:12 #evaluate#282 at /home/pkgeval/.julia/packages/MLJBase/krfwA/src/resampling/evaluate.jl:565:0 (pc: 5) evaluate at /home/pkgeval/.julia/packages/MLJBase/krfwA/src/resampling/evaluate.jl:565:0 (pc: 11) unknown function (ip: 0x74c45e4192bd) at (unknown file) _jl_invoke at /source/src/gf.c:4138:23 [inlined] ijl_apply_generic at /source/src/gf.c:4364:12 jl_apply at /source/src/julia.h:2388:12 [inlined] do_call at /source/src/interpreter.c:123:26 eval_value at /source/src/interpreter.c:243:16 eval_body at /source/src/interpreter.c:594:35 eval_body at /source/src/interpreter.c:563:21 eval_body at /source/src/interpreter.c:571:21 eval_body at /source/src/interpreter.c:571:21 eval_body at /source/src/interpreter.c:571:21 jl_interpret_toplevel_thunk at /source/src/interpreter.c:897:21 ijl_eval_thunk at /source/src/toplevel.c:768:18 jl_toplevel_eval_flex at /source/src/toplevel.c:712:26 jl_eval_toplevel_stmts at /source/src/toplevel.c:602:15 jl_toplevel_eval_flex at /source/src/toplevel.c:684:27 ijl_toplevel_eval at /source/src/toplevel.c:782:12 ijl_toplevel_eval_in at /source/src/toplevel.c:827:13 eval at ./boot.jl:521:0 (pc: 1) include_string at ./loading.jl:3132:0 (pc: 189) _jl_invoke at /source/src/gf.c:4138:23 [inlined] ijl_apply_generic at /source/src/gf.c:4364:12 _include at ./loading.jl:3192:0 (pc: 122) include at ./Base.jl:327:0 (pc: 1) IncludeInto at ./Base.jl:328:0 [inlined] run_tests at /home/pkgeval/.julia/packages/SoleModels/iRRCx/test/runtests.jl:8:0 (pc: 42) unknown function (ip: 0x74c47b5f2ca2) at (unknown file) _jl_invoke at /source/src/gf.c:4138:23 [inlined] ijl_apply_generic at /source/src/gf.c:4364:12 macro expansion at /home/pkgeval/.julia/packages/SoleModels/iRRCx/test/runtests.jl:36:0 [inlined] macro expansion at /source/usr/share/julia/stdlib/v1.14/Test/src/Test.jl:2246:0 [inlined] macro expansion at /home/pkgeval/.julia/packages/SoleModels/iRRCx/test/runtests.jl:36:0 [inlined] macro expansion at /source/usr/share/julia/stdlib/v1.14/Test/src/Test.jl:2246:0 [inlined] top-level scope at /home/pkgeval/.julia/packages/SoleModels/iRRCx/test/runtests.jl:31:0 (pc: 499) jl_invoke_oneshot at /source/src/gf.c:4173:23 ijl_eval_thunk at /source/src/toplevel.c:760:18 jl_toplevel_eval_flex at /source/src/toplevel.c:712:26 jl_eval_toplevel_stmts at /source/src/toplevel.c:602:15 jl_toplevel_eval_flex at /source/src/toplevel.c:684:27 ijl_toplevel_eval at /source/src/toplevel.c:782:12 ijl_toplevel_eval_in at /source/src/toplevel.c:827:13 eval at ./boot.jl:521:0 (pc: 1) include_string at ./loading.jl:3132:0 (pc: 207) _jl_invoke at /source/src/gf.c:4138:23 [inlined] ijl_apply_generic at /source/src/gf.c:4364:12 _include at ./loading.jl:3192:0 (pc: 122) include at ./Base.jl:327:0 (pc: 1) IncludeInto at ./Base.jl:328:0 (pc: 2) jfptr_IncludeInto_1.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4138:23 [inlined] ijl_apply_generic at /source/src/gf.c:4364:12 jl_apply at /source/src/julia.h:2388:12 [inlined] do_call at /source/src/interpreter.c:123:26 eval_value at /source/src/interpreter.c:243:16 eval_stmt_value at /source/src/interpreter.c:194:23 [inlined] eval_body at /source/src/interpreter.c:706:13 jl_interpret_toplevel_thunk at /source/src/interpreter.c:897:21 ijl_eval_thunk at /source/src/toplevel.c:768:18 jl_toplevel_eval_flex at /source/src/toplevel.c:712:26 jl_eval_toplevel_stmts at /source/src/toplevel.c:602:15 jl_toplevel_eval_flex at /source/src/toplevel.c:684:27 ijl_toplevel_eval at /source/src/toplevel.c:782:12 ijl_toplevel_eval_in at /source/src/toplevel.c:827:13 eval at ./boot.jl:521:0 (pc: 1) exec_options at ./client.jl:321:0 (pc: 425) _start at ./client.jl:596:0 (pc: 294) jfptr__start_0.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4138:23 [inlined] ijl_apply_generic at /source/src/gf.c:4364:12 jl_apply at /source/src/julia.h:2388:12 [inlined] true_main at /source/src/jlapi.c:971:29 jl_repl_entrypoint at /source/src/jlapi.c:1138:15 main at /source/cli/loader_exe.c:58:15 unknown function (ip: 0x74c4ada07249) at /lib/x86_64-linux-gnu/libc.so.6 __libc_start_main at /lib/x86_64-linux-gnu/libc.so.6 (unknown line) unknown function (ip: 0x4010b8) at /workspace/srcdir/glibc-2.17/csu/../sysdeps/x86_64/start.S unknown function (ip: (nil)) at (unknown file) ============================================================== Profile collected. A report will print at the next yield point. Disabling --trace-compile ============================================================== [ Info: For silent loading, specify `verbosity=0`. import MLJXGBoostInterface ====================================================================================== Information request received. A stacktrace will print followed by a 1.0 second profile. --trace-compile is enabled during profile collection. ====================================================================================== cmd: /opt/julia/bin/julia 1 running 0 of 1 signal (10): User defined signal 1 epoll_pwait at /lib/x86_64-linux-gnu/libc.so.6 (unknown line) uv__io_poll at /workspace/srcdir/libuv/src/unix/linux.c:1404:0 uv_run at /workspace/srcdir/libuv/src/unix/core.c:430:0 ijl_task_get_next at /source/src/scheduler.c:457:34 wait at ./task.jl:1246:0 (pc: 107) wait_forever at ./task.jl:1168:0 (pc: 4) jfptr_wait_forever_0.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4138:23 [inlined] ijl_apply_generic at /source/src/gf.c:4364:12 jl_apply at /source/src/julia.h:2388:12 [inlined] start_task at /source/src/task.c:1275:19 unknown function (ip: (nil)) at (unknown file) ============================================================== Profile collected. A report will print at the next yield point. Disabling --trace-compile ============================================================== ┌ Warning: There were no samples collected in one or more groups. │ This may be due to idle threads, or you may need to run your │ program longer (perhaps by running it multiple times), │ or adjust the delay between samples with `Profile.init()`. └ @ Profile /opt/julia/share/julia/stdlib/v1.14/Profile/src/Profile.jl:1361 Overhead ╎ [+additional indent] Count File:Line Function ========================================================= Thread 1 (default) Task 0x00007468056dcf10 Total snapshots: 430. Utilization: 0% ╎430 @Base/task.jl:1168 wait_forever() 429╎ 430 @Base/task.jl:1246 wait() ✔ ┌ Warning: There were no samples collected in one or more groups. │ This may be due to idle threads, or you may need to run your │ program longer (perhaps by running it multiple times), │ or adjust the delay between samples with `Profile.init()`. └ @ Profile /opt/julia/share/julia/stdlib/v1.14/Profile/src/Profile.jl:1361 PkgEval terminated after 2721.94s: test duration exceeded the time limit