Package evaluation to test ConformalPrediction on Julia 1.14.0-DEV.50 (b60d1db399*) started at 2025-11-10T02:06:46.420 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 9.34s ################################################################################ # Installation # Installing ConformalPrediction... Resolving package versions... Updating `~/.julia/environments/v1.14/Project.toml` [98bfc277] + ConformalPrediction v0.1.13 Updating `~/.julia/environments/v1.14/Manifest.toml` [47edcb42] + ADTypes v1.18.0 [621f4979] + AbstractFFTs v1.5.0 [7d9f7c33] + Accessors v0.1.42 [79e6a3ab] + Adapt v4.4.0 [66dad0bd] + AliasTables v1.1.3 [dce04be8] + ArgCheck v2.5.0 [4fba245c] + ArrayInterface v7.22.0 [a9b6321e] + Atomix v1.1.2 [fbb218c0] + BSON v0.3.9 [198e06fe] + BangBang v0.4.6 [9718e550] + Baselet v0.1.1 [fa961155] + CEnum v0.5.0 ⌅ [324d7699] + CategoricalArrays v0.10.8 ⌅ [af321ab8] + CategoricalDistributions v0.1.15 [082447d4] + ChainRules v1.72.6 [d360d2e6] + ChainRulesCore v1.26.0 ⌅ [3da002f7] + ColorTypes v0.11.5 [bbf7d656] + CommonSubexpressions v0.3.1 [34da2185] + Compat v4.18.1 [a33af91c] + CompositionsBase v0.1.2 [ed09eef8] + ComputationalResources v0.3.2 [98bfc277] + ConformalPrediction v0.1.13 [187b0558] + ConstructionBase v1.6.0 [6add18c4] + ContextVariablesX v0.1.3 [a8cc5b0e] + Crayons v4.1.1 [9a962f9c] + DataAPI v1.16.0 [864edb3b] + DataStructures v0.19.3 [e2d170a0] + DataValueInterfaces v1.0.0 [244e2a9f] + DefineSingletons v0.1.2 [8bb1440f] + DelimitedFiles v1.9.1 [b429d917] + DensityInterface v0.4.0 [163ba53b] + DiffResults v1.1.0 [b552c78f] + DiffRules v1.15.1 [a0c0ee7d] + DifferentiationInterface v0.7.11 [31c24e10] + Distributions v0.25.122 [ffbed154] + DocStringExtensions v0.9.5 [4e289a0a] + EnumX v1.0.5 [cc61a311] + FLoops v0.2.2 [b9860ae5] + FLoopsBase v0.1.1 [5789e2e9] + FileIO v1.17.1 [1a297f60] + FillArrays v1.15.0 [6a86dc24] + FiniteDiff v2.29.0 [53c48c17] + FixedPointNumbers v0.8.5 ⌅ [587475ba] + Flux v0.14.25 [f6369f11] + ForwardDiff v1.2.2 ⌅ [d9f16b24] + Functors v0.4.12 [0c68f7d7] + GPUArrays v11.2.6 [46192b85] + GPUArraysCore v0.2.0 [076d061b] + HashArrayMappedTries v0.2.0 [34004b35] + HypergeometricFunctions v0.3.28 [7869d1d1] + IRTools v0.4.15 ⌅ [4846b161] + InferOpt v0.6.1 [22cec73e] + InitialValues v0.3.1 [3587e190] + InverseFunctions v0.1.17 [41ab1584] + InvertedIndices v1.3.1 [92d709cd] + IrrationalConstants v0.2.6 [42fd0dbc] + IterativeSolvers v0.9.4 [82899510] + IteratorInterfaceExtensions v1.0.0 ⌅ [033835bb] + JLD2 v0.5.15 [692b3bcd] + JLLWrappers v1.7.1 [b14d175d] + JuliaVariables v0.2.4 [63c18a36] + KernelAbstractions v0.9.39 [929cbde3] + LLVM v9.4.4 [b964fa9f] + LaTeXStrings v1.4.0 ⌅ [92ad9a40] + LearnAPI v1.0.1 [d3d80556] + LineSearches v7.4.0 [7a12625a] + LinearMaps v3.11.4 [2ab3a3ac] + LogExpFunctions v0.3.29 [c2834f40] + MLCore v1.0.0 ⌃ [7e8f7934] + MLDataDevices v1.5.3 ⌃ [a7f614a8] + MLJBase v1.9.2 ⌃ [50ed68f4] + MLJEnsembles v0.4.3 ⌅ [094fc8d1] + MLJFlux v0.5.1 [6ee0df7b] + MLJLinearModels v0.10.1 [e80e1ace] + MLJModelInterface v1.12.0 [d8e11817] + MLStyle v0.4.17 [f1d291b0] + MLUtils v0.4.8 [1914dd2f] + MacroTools v0.5.16 [dbeba491] + Metalhead v0.9.5 [128add7d] + MicroCollections v0.2.0 [e1d29d7a] + Missings v1.2.0 [d41bc354] + NLSolversBase v7.10.0 [872c559c] + NNlib v0.9.31 [77ba4419] + NaNMath v1.1.3 [71a1bf82] + NameResolution v0.1.5 [0b1bfda6] + OneHotArrays v0.2.10 [429524aa] + Optim v1.13.2 ⌅ [3bd65402] + Optimisers v0.3.4 [bac558e1] + OrderedCollections v1.8.1 [90014a1f] + PDMats v0.11.36 [d96e819e] + Parameters v0.12.3 [570af359] + PartialFunctions v1.2.1 [85a6dd25] + PositiveFactorizations v0.2.4 [aea7be01] + PrecompileTools v1.3.3 [21216c6a] + Preferences v1.5.0 [8162dcfd] + PrettyPrint v0.2.0 ⌅ [08abe8d2] + PrettyTables v2.4.0 [33c8b6b6] + ProgressLogging v0.1.5 [92933f4c] + ProgressMeter v1.11.0 [43287f4e] + PtrArrays v1.3.0 [1fd47b50] + QuadGK v2.11.2 [c1ae055f] + RealDot v0.1.0 [3cdcf5f2] + RecipesBase v1.3.4 [189a3867] + Reexport v1.2.2 [42d2dcc6] + Referenceables v0.1.3 [97f35ef4] + RequiredInterfaces v0.1.7 [ae029012] + Requires v1.3.1 [79098fc4] + Rmath v0.9.0 [321657f4] + ScientificTypes v3.1.1 [30f210dd] + ScientificTypesBase v3.0.0 [7e506255] + ScopedValues v1.5.0 [efcf1570] + Setfield v1.1.2 [605ecd9f] + ShowCases v0.1.0 [699a6c99] + SimpleTraits v0.9.5 [a2af1166] + SortingAlgorithms v1.2.2 [dc90abb0] + SparseInverseSubset v0.1.2 [276daf66] + SpecialFunctions v2.6.1 [171d559e] + SplittablesBase v0.1.15 [90137ffa] + StaticArrays v1.9.15 [1e83bf80] + StaticArraysCore v1.4.4 [c062fc1d] + StatisticalMeasuresBase v0.1.3 [64bff920] + StatisticalTraits v3.5.0 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.7.1 [2913bbd2] + StatsBase v0.34.7 [4c63d2b9] + StatsFuns v1.5.2 [892a3eda] + StringManipulation v0.4.1 [09ab397b] + StructArrays v0.7.2 [3783bdb8] + TableTraits v1.0.1 [bd369af6] + Tables v1.12.1 [ac1d9e8a] + ThreadsX v0.1.12 [3bb67fe8] + TranscodingStreams v0.11.3 [28d57a85] + Transducers v0.4.85 [3a884ed6] + UnPack v1.0.2 [013be700] + UnsafeAtomics v0.3.0 ⌅ [e88e6eb3] + Zygote v0.6.77 [700de1a5] + ZygoteRules v0.2.7 [dad2f222] + LLVMExtra_jll v0.0.38+0 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [f50d1b31] + Rmath_jll v0.5.1+0 [0dad84c5] + ArgTools v1.1.2 [56f22d72] + Artifacts v1.11.0 [2a0f44e3] + Base64 v1.11.0 [ade2ca70] + Dates v1.11.0 [8ba89e20] + Distributed v1.11.0 [f43a241f] + Downloads v1.7.0 [7b1f6079] + FileWatching v1.11.0 [9fa8497b] + Future v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.12.0 [4af54fe1] + LazyArtifacts v1.11.0 [b27032c2] + LibCURL v1.0.0 [76f85450] + LibGit2 v1.11.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.13.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [a63ad114] + Mmap v1.11.0 [ca575930] + NetworkOptions v1.3.0 [44cfe95a] + Pkg v1.13.0 [de0858da] + Printf v1.11.0 [3fa0cd96] + REPL v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v1.0.0 [9e88b42a] + Serialization v1.11.0 [6462fe0b] + Sockets v1.11.0 [2f01184e] + SparseArrays v1.13.0 [f489334b] + StyledStrings v1.11.0 [4607b0f0] + SuiteSparse [fa267f1f] + TOML v1.0.3 [a4e569a6] + Tar v1.10.0 [8dfed614] + Test v1.11.0 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] + LibCURL_jll v8.16.0+0 [e37daf67] + LibGit2_jll v1.9.1+0 [29816b5a] + LibSSH2_jll v1.11.3+1 [14a3606d] + MozillaCACerts_jll v2025.11.4 [4536629a] + OpenBLAS_jll v0.3.29+0 [05823500] + OpenLibm_jll v0.8.7+0 [458c3c95] + OpenSSL_jll v3.5.4+0 [efcefdf7] + PCRE2_jll v10.47.0+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.1+2 [3161d3a3] + Zstd_jll v1.5.7+1 [8e850b90] + libblastrampoline_jll v5.15.0+0 [8e850ede] + nghttp2_jll v1.68.0+1 [3f19e933] + p7zip_jll v17.7.0+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 6.64s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... ┌ Error: Failed to use TestEnv.jl; test dependencies will not be precompiled │ exception = │ UndefVarError: `project_rel_path` not defined in `TestEnv` │ Suggestion: this global was defined as `Pkg.Operations.project_rel_path` but not assigned a value. │ Stacktrace: │ [1] get_test_dir(ctx::Pkg.Types.Context, pkgspec::PackageSpec) │ @ TestEnv ~/.julia/packages/TestEnv/nGMfF/src/julia-1.11/common.jl:75 │ [2] test_dir_has_project_file │ @ ~/.julia/packages/TestEnv/nGMfF/src/julia-1.11/common.jl:52 [inlined] │ [3] maybe_gen_project_override! │ @ ~/.julia/packages/TestEnv/nGMfF/src/julia-1.11/common.jl:83 [inlined] │ [4] activate(pkg::String; allow_reresolve::Bool) │ @ TestEnv ~/.julia/packages/TestEnv/nGMfF/src/julia-1.11/activate_set.jl:12 │ [5] activate(pkg::String) │ @ TestEnv ~/.julia/packages/TestEnv/nGMfF/src/julia-1.11/activate_set.jl:9 │ [6] top-level scope │ @ /PkgEval.jl/scripts/precompile.jl:24 │ [7] include(mod::Module, _path::String) │ @ Base ./Base.jl:309 │ [8] exec_options(opts::Base.JLOptions) │ @ Base ./client.jl:344 │ [9] _start() │ @ Base ./client.jl:577 └ @ Main /PkgEval.jl/scripts/precompile.jl:26 Precompiling package dependencies... Precompiling packages... 2534.3 ms ✓ Optimisers 11905.8 ms ✓ ChainRules 3359.3 ms ✓ StatsFuns 4582.2 ms ✓ Transducers → TransducersReferenceablesExt 2426.7 ms ✓ NNlib → NNlibSpecialFunctionsExt 2859.2 ms ✓ NNlib → NNlibForwardDiffExt 20400.3 ms ✓ MLUtils 8594.4 ms ✓ MLJLinearModels 56470.4 ms ✓ Zygote 1592.1 ms ✓ ArrayInterface → ArrayInterfaceChainRulesExt 1840.6 ms ✓ MLDataDevices → MLDataDevicesChainRulesExt 3441.7 ms ✓ StatsFuns → StatsFunsChainRulesCoreExt 1077.8 ms ✓ StatsFuns → StatsFunsInverseFunctionsExt 11921.1 ms ✓ Distributions 3985.7 ms ✓ ThreadsX 16557.3 ms ✓ StatisticalMeasuresBase 5251.8 ms ✓ MLDataDevices → MLDataDevicesMLUtilsExt 5520.3 ms ✓ DifferentiationInterface → DifferentiationInterfaceZygoteExt 5363.2 ms ✓ MLDataDevices → MLDataDevicesZygoteExt 5252.2 ms ✓ Distributions → DistributionsTestExt 4099.7 ms ✓ Distributions → DistributionsDensityInterfaceExt 4176.2 ms ✓ Distributions → DistributionsChainRulesCoreExt 7871.2 ms ✓ ScientificTypes 4380.3 ms ✓ InferOpt 23759.9 ms ✓ Flux 8105.3 ms ✓ CategoricalDistributions 26160.4 ms ✓ Metalhead 14068.7 ms ✓ MLJEnsembles 18385.7 ms ✓ MLJBase 29612.7 ms ✓ MLJFlux 31696.5 ms ✓ ConformalPrediction 31 dependencies successfully precompiled in 351 seconds. 226 already precompiled. Precompilation completed after 361.89s ################################################################################ # Testing # Testing ConformalPrediction Test Could not use exact versions of packages in manifest, re-resolving. Note: if you do not check your manifest file into source control, then you can probably ignore this message. However, if you do check your manifest file into source control, then you probably want to pass the `allow_reresolve = false` kwarg when calling the `Pkg.test` function. Installed LightGBM ─ v0.7.2 Updating `/tmp/jl_fdNZ9P/Project.toml` [4c88cf16] ↑ Aqua v0.8.4 ⇒ v0.8.14 [5224ae11] ↑ CompatHelperLocal v0.1.26 ⇒ v0.1.27 [98bfc277] + ConformalPrediction v0.1.13 [e30172f5] ↑ Documenter v1.3.0 ⇒ v1.15.0 ⌅ [f6006082] ↑ EvoTrees v0.16.6 ⇒ v0.16.9 ⌅ [7acf609c] ↑ LightGBM v0.6.1 ⇒ v0.7.2 ⌅ [add582a8] ↑ MLJ v0.19.5 ⇒ v0.20.9 ⌃ [c6f25543] ↑ MLJDecisionTreeInterface v0.4.1 ⇒ v0.4.2 ⌅ [094fc8d1] ↑ MLJFlux v0.4.0 ⇒ v0.5.1 [6ee0df7b] ↑ MLJLinearModels v0.10.0 ⇒ v0.10.1 [e80e1ace] ↑ MLJModelInterface v1.9.5 ⇒ v1.12.0 [91a5bcdd] ↑ Plots v1.40.2 ⇒ v1.41.1 [bd7198b4] ↑ TaijaPlotting v1.0.7 ⇒ v1.3.0 [8dfed614] ~ Test ⇒ v1.11.0 Updating `/tmp/jl_fdNZ9P/Manifest.toml` [47edcb42] + ADTypes v1.18.0 [da404889] ↑ ARFFFiles v1.4.1 ⇒ v1.5.0 [7d9f7c33] + Accessors v0.1.42 [79e6a3ab] ↑ Adapt v4.0.3 ⇒ v4.4.0 [66dad0bd] + AliasTables v1.1.3 [4c88cf16] ↑ Aqua v0.8.4 ⇒ v0.8.14 [dce04be8] ↑ ArgCheck v2.3.0 ⇒ v2.5.0 [ec485272] ↑ ArnoldiMethod v0.2.0 ⇒ v0.4.0 [4fba245c] ↑ ArrayInterface v7.9.0 ⇒ v7.22.0 [a9b6321e] ↑ Atomix v0.1.0 ⇒ v1.1.2 [a963bdd2] - AtomsBase v0.3.5 [ab4f0b2a] - BFloat16s v0.4.2 [198e06fe] ↑ BangBang v0.3.40 ⇒ v0.4.6 [6e4b80f9] - BenchmarkTools v1.5.0 [d1d4a3ce] ↑ BitFlags v0.1.8 ⇒ v0.1.9 [e1450e63] - BufferedStreams v1.2.1 [336ed68f] - CSV v0.10.13 [052768ef] - CUDA v5.2.0 [1af6417a] - CUDA_Runtime_Discovery v0.2.3 [49dc2e85] - Calculus v0.5.1 ⌅ [af321ab8] ↑ CategoricalDistributions v0.1.14 ⇒ v0.1.15 ⌅ [8e462317] + CausalInference v0.18.0 [082447d4] ↑ ChainRules v1.63.0 ⇒ v1.72.6 [d360d2e6] ↑ ChainRulesCore v1.23.0 ⇒ v1.26.0 [46823bd8] - Chemfiles v0.10.41 [523fee87] - CodecBzip2 v0.8.2 [944b1d66] ↑ CodecZlib v0.7.4 ⇒ v0.7.8 [35d6a980] ↑ ColorSchemes v3.24.0 ⇒ v3.31.0 ⌅ [3da002f7] ↑ ColorTypes v0.11.4 ⇒ v0.11.5 [5ae59095] ↑ Colors v0.12.10 ⇒ v0.13.1 [861a8166] ↑ Combinatorics v1.0.2 ⇒ v1.0.3 [bbf7d656] ↑ CommonSubexpressions v0.3.0 ⇒ v0.3.1 [34da2185] ↑ Compat v4.14.0 ⇒ v4.18.1 [5224ae11] ↑ CompatHelperLocal v0.1.26 ⇒ v0.1.27 [f0e56b4a] ↑ ConcurrentUtilities v2.4.1 ⇒ v2.5.0 [98bfc277] ↑ ConformalPrediction v0.1.6 ⇒ v0.1.13 [187b0558] ↑ ConstructionBase v1.5.5 ⇒ v1.6.0 [d38c429a] ↑ Contour v0.6.2 ⇒ v0.6.3 [2f13d31b] ↑ CounterfactualExplanations v0.1.31 ⇒ v1.4.5 [124859b0] - DataDeps v0.7.13 [a93c6f00] ↑ DataFrames v1.6.1 ⇒ v1.8.1 [864edb3b] ↑ DataStructures v0.18.18 ⇒ v0.19.3 [b429d917] + DensityInterface v0.4.0 [a0c0ee7d] + DifferentiationInterface v0.7.11 [b4f34e82] ↑ Distances v0.10.11 ⇒ v0.10.12 [31c24e10] ↑ Distributions v0.25.107 ⇒ v0.25.122 [ffbed154] ↑ DocStringExtensions v0.9.3 ⇒ v0.9.5 [e30172f5] ↑ Documenter v1.3.0 ⇒ v1.15.0 [fa6b7ba4] - DualNumbers v0.6.8 [f446124b] + EnergySamplers v1.0.3 [4e289a0a] + EnumX v1.0.5 ⌅ [f6006082] ↑ EvoTrees v0.16.6 ⇒ v0.16.9 [460bff9d] ↑ ExceptionUnwrapping v0.1.10 ⇒ v0.1.11 [e2ba6199] - ExprTools v0.1.10 [411431e0] ↑ Extents v0.1.2 ⇒ v0.1.6 [c87230d0] ↑ FFMPEG v0.4.1 ⇒ v0.4.5 [cc61a311] ↑ FLoops v0.2.1 ⇒ v0.2.2 [33837fe5] + FeatureSelection v0.2.4 [5789e2e9] ↑ FileIO v1.16.3 ⇒ v1.17.1 [48062228] ↑ FilePathsBase v0.9.21 ⇒ v0.9.24 [1a297f60] ↑ FillArrays v1.9.3 ⇒ v1.15.0 [6a86dc24] ↑ FiniteDiff v2.23.0 ⇒ v2.29.0 [53c48c17] ↑ FixedPointNumbers v0.8.4 ⇒ v0.8.5 ⌅ [587475ba] ↑ Flux v0.14.14 ⇒ v0.14.25 [1fa38f19] ↑ Format v1.3.6 ⇒ v1.3.7 [f6369f11] ↑ ForwardDiff v0.10.36 ⇒ v1.2.2 ⌅ [d9f16b24] ↑ Functors v0.4.8 ⇒ v0.4.12 [0c68f7d7] ↑ GPUArrays v10.0.2 ⇒ v11.2.6 [46192b85] ↑ GPUArraysCore v0.1.6 ⇒ v0.2.0 [61eb1bfa] - GPUCompiler v0.25.0 [28b8d3ca] ↑ GR v0.73.3 ⇒ v0.73.18 [92fee26a] - GZip v0.6.2 [cf35fbd7] - GeoInterface v1.3.3 [5c1252a2] ↑ GeometryBasics v0.4.10 ⇒ v0.5.10 [d7ba0133] ↑ Git v1.3.1 ⇒ v1.5.0 [c27321d9] - Glob v1.3.1 [86223c79] ↑ Graphs v1.9.0 ⇒ v1.13.1 [f67ccb44] - HDF5 v0.17.1 [cd3eb016] ↑ HTTP v1.10.4 ⇒ v1.10.19 [076d061b] + HashArrayMappedTries v0.2.0 [34004b35] ↑ HypergeometricFunctions v0.3.23 ⇒ v0.3.28 ⌅ [b5f81e59] ↑ IOCapture v0.2.4 ⇒ v0.2.5 [7869d1d1] ↑ IRTools v0.4.12 ⇒ v0.4.15 [c817782e] - ImageBase v0.1.7 [a09fc81d] - ImageCore v0.10.2 [4e3cecfd] - ImageShow v0.3.8 ⌅ [4846b161] + InferOpt v0.6.1 [d25df0c9] ↑ Inflate v0.1.4 ⇒ v0.1.5 [842dd82b] ↑ InlineStrings v1.4.0 ⇒ v1.4.5 [7d512f48] - InternedStrings v0.7.0 [3587e190] + InverseFunctions v0.1.17 [41ab1584] ↑ InvertedIndices v1.3.0 ⇒ v1.3.1 [92d709cd] ↑ IrrationalConstants v0.2.2 ⇒ v0.2.6 ⌅ [033835bb] ↑ JLD2 v0.4.46 ⇒ v0.5.15 [1019f520] ↑ JLFzf v0.1.7 ⇒ v0.1.11 [692b3bcd] ↑ JLLWrappers v1.5.0 ⇒ v1.7.1 [0f8b85d8] - JSON3 v1.14.0 [63c18a36] ↑ KernelAbstractions v0.9.18 ⇒ v0.9.39 [ec8451be] + KernelFunctions v0.10.66 [929cbde3] ↑ LLVM v6.6.1 ⇒ v9.4.4 [8b046642] - LLVMLoopInfo v1.0.0 [8ac3fa9e] + LRUCache v1.6.2 [b964fa9f] ↑ LaTeXStrings v1.3.1 ⇒ v1.4.0 [c52c1a26] ↑ LaplaceRedux v0.1.4 ⇒ v1.2.0 [23fbe1c1] ↑ Latexify v0.16.2 ⇒ v0.16.10 [0e77f7df] ↑ LazilyInitializedFields v1.2.2 ⇒ v1.3.0 [8cdb02fc] - LazyModules v0.3.1 ⌅ [92ad9a40] + LearnAPI v1.0.1 ⌅ [7acf609c] ↑ LightGBM v0.6.1 ⇒ v0.7.2 [d3d80556] ↑ LineSearches v7.2.0 ⇒ v7.4.0 [7a12625a] ↑ LinearMaps v3.11.2 ⇒ v3.11.4 [70f5e60a] + LinkedLists v0.1.1 [2ab3a3ac] ↑ LogExpFunctions v0.3.27 ⇒ v0.3.29 [aa2f6b4e] + LogarithmicNumbers v1.4.1 [e6f89c97] ↑ LoggingExtras v1.0.3 ⇒ v1.2.0 [30fc2ffe] - LossFunctions v0.11.1 [23992714] - MAT v0.10.6 [c2834f40] + MLCore v1.0.0 ⌃ [7e8f7934] + MLDataDevices v1.5.3 [eb30cadb] - MLDatasets v0.7.14 ⌅ [64a0f543] ↑ MLFlowClient v0.4.6 ⇒ v0.5.1 ⌅ [add582a8] ↑ MLJ v0.19.5 ⇒ v0.20.9 [45f359ea] + MLJBalancing v0.1.5 ⌃ [a7f614a8] ↑ MLJBase v0.21.14 ⇒ v1.9.2 ⌃ [c6f25543] ↑ MLJDecisionTreeInterface v0.4.1 ⇒ v0.4.2 ⌃ [50ed68f4] ↑ MLJEnsembles v0.3.3 ⇒ v0.4.3 [7b7b8358] ↑ MLJFlow v0.1.1 ⇒ v0.5.0 ⌅ [094fc8d1] ↑ MLJFlux v0.4.0 ⇒ v0.5.1 [614be32b] ↑ MLJIteration v0.5.1 ⇒ v0.6.4 [6ee0df7b] ↑ MLJLinearModels v0.10.0 ⇒ v0.10.1 [e80e1ace] ↑ MLJModelInterface v1.9.5 ⇒ v1.12.0 ⌅ [d491faf4] ↑ MLJModels v0.16.16 ⇒ v0.17.9 [03970b2e] ↑ MLJTuning v0.7.4 ⇒ v0.8.8 [f1d291b0] ↑ MLUtils v0.4.4 ⇒ v0.4.8 [3da0fdf6] - MPIPreferences v0.1.10 [1914dd2f] ↑ MacroTools v0.5.13 ⇒ v0.5.16 [06eb3307] - ManifoldLearning v0.9.0 [dbb5928d] - MappedArrays v0.4.2 [b8f27783] - MathOptInterface v1.27.0 [442fdcdd] ↑ Measures v0.3.2 ⇒ v0.3.3 [6fafb56a] + Memoization v0.2.2 [626554b9] + MetaGraphs v0.8.1 [dbeba491] ↑ Metalhead v0.9.3 ⇒ v0.9.5 [128add7d] ↑ MicroCollections v0.1.4 ⇒ v0.2.0 [e1d29d7a] ↑ Missings v1.1.0 ⇒ v1.2.0 [e94cdb99] - MosaicViews v0.3.4 [6f286f6a] ↑ MultivariateStats v0.9.0 ⇒ v0.10.3 [d8a4904e] - MutableArithmetics v1.4.1 [d41bc354] ↑ NLSolversBase v7.8.3 ⇒ v7.10.0 [872c559c] ↑ NNlib v0.9.12 ⇒ v0.9.31 [15e1cf62] - NPZ v0.4.3 [5da4648a] - NVTX v0.3.4 [77ba4419] ↑ NaNMath v1.0.2 ⇒ v1.1.3 [b8a86587] ↑ NearestNeighbors v0.4.16 ⇒ v0.4.22 [46757867] ↑ NetworkLayout v0.4.6 ⇒ v0.4.10 [6fe1bfb0] ↑ OffsetArrays v1.13.0 ⇒ v1.17.0 [0b1bfda6] ↑ OneHotArrays v0.2.5 ⇒ v0.2.10 [8b6db2d4] ↑ OpenML v0.3.1 ⇒ v0.3.2 [4d8831e6] ↑ OpenSSL v1.4.2 ⇒ v1.6.0 [429524aa] ↑ Optim v1.9.2 ⇒ v1.13.2 ⌅ [3bd65402] ↑ Optimisers v0.3.2 ⇒ v0.3.4 [bac558e1] ↑ OrderedCollections v1.6.3 ⇒ v1.8.1 [90014a1f] ↑ PDMats v0.11.31 ⇒ v0.11.36 [5432bcbf] - PaddedViews v0.5.12 [69de0a69] ↑ Parsers v2.8.1 ⇒ v2.8.3 [570af359] ↑ PartialFunctions v1.2.0 ⇒ v1.2.1 [7b2266bf] - PeriodicTable v1.2.1 [fbb45041] - Pickle v0.3.3 [b98c9c47] - Pipe v1.3.0 [ccf2f8ad] ↑ PlotThemes v3.1.0 ⇒ v3.3.0 [995b91a9] ↑ PlotUtils v1.4.1 ⇒ v1.4.4 [91a5bcdd] ↑ Plots v1.40.2 ⇒ v1.41.1 [aea7be01] ↑ PrecompileTools v1.2.1 ⇒ v1.3.3 [21216c6a] ↑ Preferences v1.4.3 ⇒ v1.5.0 ⌅ [08abe8d2] ↑ PrettyTables v2.3.1 ⇒ v2.4.0 [33c8b6b6] ↑ ProgressLogging v0.1.4 ⇒ v0.1.5 [92933f4c] ↑ ProgressMeter v1.10.0 ⇒ v1.11.0 [43287f4e] + PtrArrays v1.3.0 [1fd47b50] ↑ QuadGK v2.9.4 ⇒ v2.11.2 [74087812] - Random123 v1.7.0 [e6cf234a] - RandomNumbers v1.5.3 [42d2dcc6] + Referenceables v0.1.3 [97f35ef4] + RequiredInterfaces v0.1.7 [ae029012] ↑ Requires v1.3.0 ⇒ v1.3.1 [79098fc4] ↑ Rmath v0.7.1 ⇒ v0.9.0 [321657f4] ↑ ScientificTypes v3.0.2 ⇒ v3.1.1 [7e506255] + ScopedValues v1.5.0 [6c6a2e73] ↑ Scratch v1.2.1 ⇒ v1.3.0 [91c51154] ↑ SentinelArrays v1.4.1 ⇒ v1.4.8 [efcf1570] ↑ Setfield v1.1.1 ⇒ v1.1.2 [777ac1f9] ↑ SimpleBufferStream v1.1.0 ⇒ v1.2.0 [699a6c99] ↑ SimpleTraits v0.9.4 ⇒ v0.9.5 [a2af1166] ↑ SortingAlgorithms v1.2.1 ⇒ v1.2.2 [276daf66] ↑ SpecialFunctions v2.3.1 ⇒ v2.6.1 [860ef19b] ↑ StableRNGs v1.0.1 ⇒ v1.0.3 [cae243ae] - StackViews v0.1.1 [90137ffa] ↑ StaticArrays v1.9.3 ⇒ v1.9.15 [1e83bf80] ↑ StaticArraysCore v1.4.2 ⇒ v1.4.4 ⌅ [a19d573c] + StatisticalMeasures v0.2.1 [c062fc1d] + StatisticalMeasuresBase v0.1.3 [64bff920] ↑ StatisticalTraits v3.2.0 ⇒ v3.5.0 [10745b16] ↑ Statistics v1.10.0 ⇒ v1.11.1 [82ae8749] ↑ StatsAPI v1.7.0 ⇒ v1.7.1 [2913bbd2] ↑ StatsBase v0.33.21 ⇒ v0.34.7 [4c63d2b9] ↑ StatsFuns v1.3.1 ⇒ v1.5.2 [5e0ebb24] - Strided v1.2.3 [69024149] - StringEncodings v0.3.7 [892a3eda] ↑ StringManipulation v0.3.4 ⇒ v0.4.1 [09ab397b] ↑ StructArrays v0.6.18 ⇒ v0.7.2 [856f2bd8] - StructTypes v1.10.0 [bd369af6] ↑ Tables v1.11.1 ⇒ v1.12.1 [3eeacb1d] + TabularDisplay v1.3.0 [10284c91] + TaijaBase v1.2.3 [bd7198b4] ↑ TaijaPlotting v1.0.7 ⇒ v1.3.0 [ac1d9e8a] + ThreadsX v0.1.12 [a759f4b9] - TimerOutputs v0.5.23 [3bb67fe8] ↑ TranscodingStreams v0.10.5 ⇒ v0.11.3 [28d57a85] ↑ Transducers v0.4.80 ⇒ v0.4.85 [592b5752] + Trapz v2.0.3 [bc48ee85] ↑ Tullio v0.3.7 ⇒ v0.3.8 [9d95972d] - TupleTools v1.5.0 [5c2747f8] ↑ URIs v1.5.1 ⇒ v1.6.1 [1986cc42] - Unitful v1.19.0 [a7773ee8] - UnitfulAtomic v1.0.0 [45397f5d] - UnitfulLatexify v1.6.3 [013be700] ↑ UnsafeAtomics v0.2.1 ⇒ v0.3.0 [d80eeb9a] - UnsafeAtomicsLLVM v0.1.3 [ea10d353] - WeakRefStrings v1.4.2 [76eceee3] - WorkerUtilities v1.6.1 [a5390f91] - ZipFile v0.10.1 ⌅ [e88e6eb3] ↑ Zygote v0.6.69 ⇒ v0.6.77 [700de1a5] ↑ ZygoteRules v0.2.5 ⇒ v0.2.7 [02a925ec] - cuDNN v1.3.0 [6e34b625] ↑ Bzip2_jll v1.0.8+1 ⇒ v1.0.9+0 [4ee394cb] - CUDA_Driver_jll v0.7.0+1 [76a88914] - CUDA_Runtime_jll v0.11.1+0 [62b44479] - CUDNN_jll v8.9.4+0 [83423d85] ↑ Cairo_jll v1.18.0+1 ⇒ v1.18.5+0 [78a364fa] - Chemfiles_jll v0.10.4+0 [ee1fde0b] + Dbus_jll v1.16.2+0 [2702e6a9] ↑ EpollShim_jll v0.0.20230411+0 ⇒ v0.0.20230411+1 [2e619515] ↑ Expat_jll v2.5.0+0 ⇒ v2.7.3+0 [b22a6f82] ↑ FFMPEG_jll v4.4.4+1 ⇒ v8.0.0+0 [a3f928ae] ↑ Fontconfig_jll v2.13.93+0 ⇒ v2.17.1+0 [d7e528f0] ↑ FreeType2_jll v2.13.1+0 ⇒ v2.13.4+0 [559328eb] ↑ FriBidi_jll v1.0.10+0 ⇒ v1.0.17+0 [0656b61e] ↑ GLFW_jll v3.3.9+0 ⇒ v3.4.0+2 [d2c73de3] ↑ GR_jll v0.73.3+0 ⇒ v0.73.18+0 [b0724c58] + GettextRuntime_jll v0.22.4+0 [78b55507] - Gettext_jll v0.21.0+0 [61579ee1] + Ghostscript_jll v9.55.1+0 [020c3dae] + Git_LFS_jll v3.7.0+0 [f8c6e375] ↑ Git_jll v2.44.0+1 ⇒ v2.51.3+0 [7746bdde] ↑ Glib_jll v2.80.0+0 ⇒ v2.86.0+0 [3b182d85] ↑ Graphite2_jll v1.3.14+0 ⇒ v1.3.15+0 [0234f1f7] - HDF5_jll v1.14.2+1 [2e76f6c2] ↑ HarfBuzz_jll v2.8.1+1 ⇒ v8.5.1+0 [e33a78d0] - Hwloc_jll v2.10.0+0 [aacddb02] ↑ JpegTurbo_jll v3.0.2+0 ⇒ v3.1.3+0 [9c1d0b0a] - JuliaNVTXCallbacks_jll v0.2.1+0 [c1c5ebd0] ↑ LAME_jll v3.100.1+0 ⇒ v3.100.3+0 [88015f11] ↑ LERC_jll v3.0.0+1 ⇒ v4.0.1+0 [dad2f222] ↑ LLVMExtra_jll v0.0.29+0 ⇒ v0.0.38+0 [1d63c593] ↑ LLVMOpenMP_jll v15.0.7+0 ⇒ v18.1.8+0 [dd4b983a] ↑ LZO_jll v2.10.1+0 ⇒ v2.10.3+0 [e9f186c6] ↑ Libffi_jll v3.2.2+1 ⇒ v3.4.7+0 [d4300ac3] - Libgcrypt_jll v1.8.7+0 [7e76a0d4] ↑ Libglvnd_jll v1.6.0+0 ⇒ v1.7.1+1 [7add5ba3] - Libgpg_error_jll v1.42.0+0 [94ce4f54] ↑ Libiconv_jll v1.17.0+0 ⇒ v1.18.0+0 [4b2f31a3] ↑ Libmount_jll v2.39.3+0 ⇒ v2.41.2+0 [89763e89] ↑ Libtiff_jll v4.5.1+1 ⇒ v4.7.2+0 [38a345b3] ↑ Libuuid_jll v2.39.3+1 ⇒ v2.41.2+0 ⌅ [0e4427ef] + LightGBM_jll v3.3.5+1 [7cb0a576] - MPICH_jll v4.2.0+0 [f1f71cc9] - MPItrampoline_jll v5.3.2+0 [c8ffd9c3] ↑ MbedTLS_jll v2.28.2+1 ⇒ v2.28.10+0 [9237b28f] - MicrosoftMPI_jll v10.1.4+2 [e98f9f5b] - NVTX_jll v3.1.0+2 [e7412a2a] ↑ Ogg_jll v1.3.5+1 ⇒ v1.3.6+0 [fe0851c0] - OpenMPI_jll v5.0.2+0 [9bd350c2] + OpenSSH_jll v10.2.1+0 [efe28fd5] ↑ OpenSpecFun_jll v0.5.5+0 ⇒ v0.5.6+0 [91d4177d] ↑ Opus_jll v1.3.2+0 ⇒ v1.5.2+0 [32165bc3] - PMIx_jll v4.2.7+0 [36c8627f] + Pango_jll v1.56.4+0 ⌅ [30392449] ↑ Pixman_jll v0.42.2+0 ⇒ v0.44.2+0 [c0090381] ↑ Qt6Base_jll v6.5.3+1 ⇒ v6.8.2+2 [629bc702] + Qt6Declarative_jll v6.8.2+1 [ce943373] + Qt6ShaderTools_jll v6.8.2+1 [e99dba38] + Qt6Wayland_jll v6.8.2+2 [f50d1b31] ↑ Rmath_jll v0.4.0+0 ⇒ v0.5.1+0 [a2964d1f] ↑ Wayland_jll v1.21.0+1 ⇒ v1.24.0+0 [2381bf8a] - Wayland_protocols_jll v1.31.0+0 [02c8fc9c] - XML2_jll v2.12.5+0 [aed1982a] - XSLT_jll v1.1.34+0 [ffd25f8a] ↑ XZ_jll v5.6.1+0 ⇒ v5.8.1+0 [f67eecfb] ↑ Xorg_libICE_jll v1.0.10+1 ⇒ v1.1.2+0 [c834827a] ↑ Xorg_libSM_jll v1.2.3+0 ⇒ v1.2.6+0 [4f6342f7] ↑ Xorg_libX11_jll v1.8.6+0 ⇒ v1.8.12+0 [0c0b7dd1] ↑ Xorg_libXau_jll v1.0.11+0 ⇒ v1.0.13+0 [935fb764] ↑ Xorg_libXcursor_jll v1.2.0+4 ⇒ v1.2.4+0 [a3789734] ↑ Xorg_libXdmcp_jll v1.1.4+0 ⇒ v1.1.6+0 [1082639a] ↑ Xorg_libXext_jll v1.3.4+4 ⇒ v1.3.7+0 [d091e8ba] ↑ Xorg_libXfixes_jll v5.0.3+4 ⇒ v6.0.2+0 [a51aa0fd] ↑ Xorg_libXi_jll v1.7.10+4 ⇒ v1.8.3+0 [d1454406] ↑ Xorg_libXinerama_jll v1.1.4+4 ⇒ v1.1.6+0 [ec84b674] ↑ Xorg_libXrandr_jll v1.5.2+4 ⇒ v1.5.5+0 [ea2f1a96] ↑ Xorg_libXrender_jll v0.9.10+4 ⇒ v0.9.12+0 [14d82f49] - Xorg_libpthread_stubs_jll v0.1.1+0 [c7cfdc94] ↑ Xorg_libxcb_jll v1.15.0+0 ⇒ v1.17.1+0 [cc61e674] ↑ Xorg_libxkbfile_jll v1.1.2+0 ⇒ v1.1.3+0 [e920d4aa] ↑ Xorg_xcb_util_cursor_jll v0.1.4+0 ⇒ v0.1.6+0 [12413925] ↑ Xorg_xcb_util_image_jll v0.4.0+1 ⇒ v0.4.1+0 [2def613f] ↑ Xorg_xcb_util_jll v0.4.0+1 ⇒ v0.4.1+0 [975044d2] ↑ Xorg_xcb_util_keysyms_jll v0.4.0+1 ⇒ v0.4.1+0 [0d47668e] ↑ Xorg_xcb_util_renderutil_jll v0.3.9+1 ⇒ v0.3.10+0 [c22f9ab0] ↑ Xorg_xcb_util_wm_jll v0.4.1+1 ⇒ v0.4.2+0 [35661453] ↑ Xorg_xkbcomp_jll v1.4.6+0 ⇒ v1.4.7+0 [33bec58e] ↑ Xorg_xkeyboard_config_jll v2.39.0+0 ⇒ v2.44.0+0 [c5fb5394] ↑ Xorg_xtrans_jll v1.5.0+0 ⇒ v1.6.0+0 [35ca27e7] ↑ eudev_jll v3.2.9+0 ⇒ v3.2.14+0 [214eeab7] ↑ fzf_jll v0.43.0+0 ⇒ v0.61.1+0 [1a1c6b14] - gperf_jll v3.1.1+0 [477f73a3] - libaec_jll v1.1.2+0 [a4ae2306] ↑ libaom_jll v3.4.0+0 ⇒ v3.13.1+0 [0ac62f75] ↑ libass_jll v0.15.1+0 ⇒ v0.17.4+0 [1183f4f0] + libdecor_jll v0.2.2+0 [2db6ffa8] ↑ libevdev_jll v1.11.0+0 ⇒ v1.13.4+0 [1080aeaf] - libevent_jll v2.1.13+1 [f638f0a6] ↑ libfdk_aac_jll v2.0.2+0 ⇒ v2.0.4+0 [36db933b] ↑ libinput_jll v1.18.0+0 ⇒ v1.28.1+0 [b53b4c65] ↑ libpng_jll v1.6.43+1 ⇒ v1.6.50+0 [f27f6e37] ↑ libvorbis_jll v1.3.7+1 ⇒ v1.3.8+0 [009596ad] ↑ mtdev_jll v1.1.6+0 ⇒ v1.1.7+0 [eb928a42] - prrte_jll v3.0.2+0 [1270edf5] ↑ x264_jll v2021.5.5+0 ⇒ v10164.0.1+0 [dfaa095f] ↑ x265_jll v3.5.0+0 ⇒ v4.1.0+0 [d8fb68d0] ↑ xkbcommon_jll v1.4.1+1 ⇒ v1.9.2+0 [0dad84c5] ↑ ArgTools v1.1.1 ⇒ v1.1.2 [56f22d72] ~ Artifacts ⇒ v1.11.0 [2a0f44e3] ~ Base64 ⇒ v1.11.0 [ade2ca70] ~ Dates ⇒ v1.11.0 [8ba89e20] ~ Distributed ⇒ v1.11.0 [f43a241f] ↑ Downloads v1.6.0 ⇒ v1.7.0 [7b1f6079] ~ FileWatching ⇒ v1.11.0 [9fa8497b] ~ Future ⇒ v1.11.0 [b77e0a4c] ~ InteractiveUtils ⇒ v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.12.0 [4af54fe1] ~ LazyArtifacts ⇒ v1.11.0 [b27032c2] ↑ LibCURL v0.6.4 ⇒ v1.0.0 [76f85450] ~ LibGit2 ⇒ v1.11.0 [8f399da3] ~ Libdl ⇒ v1.11.0 [37e2e46d] ~ LinearAlgebra ⇒ v1.13.0 [56ddb016] ~ Logging ⇒ v1.11.0 [d6f4376e] ~ Markdown ⇒ v1.11.0 [a63ad114] ~ Mmap ⇒ v1.11.0 [ca575930] ↑ NetworkOptions v1.2.0 ⇒ v1.3.0 [44cfe95a] ↑ Pkg v1.10.0 ⇒ v1.13.0 [de0858da] ~ Printf ⇒ v1.11.0 [9abbd945] - Profile [3fa0cd96] ~ REPL ⇒ v1.11.0 [9a3f8284] ~ Random ⇒ v1.11.0 [ea8e919c] ↑ SHA v0.7.0 ⇒ v1.0.0 [9e88b42a] ~ Serialization ⇒ v1.11.0 [1a1011a3] ~ SharedArrays ⇒ v1.11.0 [6462fe0b] ~ Sockets ⇒ v1.11.0 [2f01184e] ↑ SparseArrays v1.10.0 ⇒ v1.13.0 [f489334b] + StyledStrings v1.11.0 [8dfed614] ~ Test ⇒ v1.11.0 [cf7118a7] ~ UUIDs ⇒ v1.11.0 [4ec0a83e] ~ Unicode ⇒ v1.11.0 [e66e0078] ↑ CompilerSupportLibraries_jll v1.1.0+0 ⇒ v1.3.0+1 [deac9b47] ↑ LibCURL_jll v8.4.0+0 ⇒ v8.16.0+0 [e37daf67] ↑ LibGit2_jll v1.6.4+0 ⇒ v1.9.1+0 [29816b5a] ↑ LibSSH2_jll v1.11.0+1 ⇒ v1.11.3+1 [14a3606d] ↑ MozillaCACerts_jll v2023.1.10 ⇒ v2025.11.4 [4536629a] ↑ OpenBLAS_jll v0.3.23+4 ⇒ v0.3.29+0 [05823500] ↑ OpenLibm_jll v0.8.1+2 ⇒ v0.8.7+0 [458c3c95] ↑ OpenSSL_jll v3.0.13+0 ⇒ v3.5.4+0 [efcefdf7] ↑ PCRE2_jll v10.42.0+1 ⇒ v10.47.0+0 [bea87d4a] ↑ SuiteSparse_jll v7.2.1+1 ⇒ v7.10.1+0 [83775a58] ↑ Zlib_jll v1.2.13+1 ⇒ v1.3.1+2 [3161d3a3] ↑ Zstd_jll v1.5.5+0 ⇒ v1.5.7+1 [8e850b90] ↑ libblastrampoline_jll v5.8.0+1 ⇒ v5.15.0+0 [8e850ede] ↑ nghttp2_jll v1.52.0+1 ⇒ v1.68.0+1 [3f19e933] ↑ p7zip_jll v17.4.0+2 ⇒ v17.7.0+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` Building LightGBM → `~/.julia/scratchspaces/44cfe95a-1eb2-52ea-b672-e2afdf69b78f/02375e29918ccdee94d72459ec37b0989709dbbb/build.log` Test Successfully re-resolved Status `/tmp/jl_fdNZ9P/Project.toml` [4c88cf16] Aqua v0.8.14 [5224ae11] CompatHelperLocal v0.1.27 [98bfc277] ConformalPrediction v0.1.13 [7806a523] DecisionTree v0.12.4 [e30172f5] Documenter v1.15.0 ⌅ [f6006082] EvoTrees v0.16.9 ⌅ [7acf609c] LightGBM v0.7.2 ⌅ [add582a8] MLJ v0.20.9 ⌃ [c6f25543] MLJDecisionTreeInterface v0.4.2 ⌅ [094fc8d1] MLJFlux v0.5.1 [6ee0df7b] MLJLinearModels v0.10.1 [e80e1ace] MLJModelInterface v1.12.0 [636a865e] NearestNeighborModels v0.2.3 [91a5bcdd] Plots v1.41.1 [bd7198b4] TaijaPlotting v1.3.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_fdNZ9P/Manifest.toml` [47edcb42] ADTypes v1.18.0 [a4c015fc] ANSIColoredPrinters v0.0.1 [da404889] ARFFFiles v1.5.0 [621f4979] AbstractFFTs v1.5.0 [1520ce14] AbstractTrees v0.4.5 [7d9f7c33] Accessors v0.1.42 [79e6a3ab] Adapt v4.4.0 [66dad0bd] AliasTables v1.1.3 [4c88cf16] Aqua v0.8.14 [dce04be8] ArgCheck v2.5.0 [ec485272] ArnoldiMethod v0.4.0 [7d9fca2a] Arpack v0.5.4 [4fba245c] ArrayInterface v7.22.0 [a9b6321e] Atomix v1.1.2 [fbb218c0] BSON v0.3.9 [198e06fe] BangBang v0.4.6 [9718e550] Baselet v0.1.1 [d1d4a3ce] BitFlags v0.1.9 [fa961155] CEnum v0.5.0 ⌅ [324d7699] CategoricalArrays v0.10.8 ⌅ [af321ab8] CategoricalDistributions v0.1.15 ⌅ [8e462317] CausalInference v0.18.0 [082447d4] ChainRules v1.72.6 [d360d2e6] ChainRulesCore v1.26.0 [944b1d66] CodecZlib v0.7.8 [35d6a980] ColorSchemes v3.31.0 ⌅ [3da002f7] ColorTypes v0.11.5 ⌃ [c3611d14] ColorVectorSpace v0.10.0 [5ae59095] Colors v0.13.1 [861a8166] Combinatorics v1.0.3 [bbf7d656] CommonSubexpressions v0.3.1 [34da2185] Compat v4.18.1 [5224ae11] CompatHelperLocal v0.1.27 [a33af91c] CompositionsBase v0.1.2 [ed09eef8] ComputationalResources v0.3.2 [f0e56b4a] ConcurrentUtilities v2.5.0 [98bfc277] ConformalPrediction v0.1.13 [187b0558] ConstructionBase v1.6.0 [6add18c4] ContextVariablesX v0.1.3 [d38c429a] Contour v0.6.3 [2f13d31b] CounterfactualExplanations v1.4.5 [a8cc5b0e] Crayons v4.1.1 [9a962f9c] DataAPI v1.16.0 [a93c6f00] DataFrames v1.8.1 [864edb3b] DataStructures v0.19.3 [e2d170a0] DataValueInterfaces v1.0.0 [7806a523] DecisionTree v0.12.4 [244e2a9f] DefineSingletons v0.1.2 [8bb1440f] DelimitedFiles v1.9.1 [b429d917] DensityInterface v0.4.0 [163ba53b] DiffResults v1.1.0 [b552c78f] DiffRules v1.15.1 [a0c0ee7d] DifferentiationInterface v0.7.11 [b4f34e82] Distances v0.10.12 [31c24e10] Distributions v0.25.122 [ffbed154] DocStringExtensions v0.9.5 [e30172f5] Documenter v1.15.0 [792122b4] EarlyStopping v0.3.0 [f446124b] EnergySamplers v1.0.3 [4e289a0a] EnumX v1.0.5 ⌅ [f6006082] EvoTrees v0.16.9 [460bff9d] ExceptionUnwrapping v0.1.11 [411431e0] Extents v0.1.6 [c87230d0] FFMPEG v0.4.5 [cc61a311] FLoops v0.2.2 [b9860ae5] FLoopsBase v0.1.1 [33837fe5] FeatureSelection v0.2.4 [5789e2e9] FileIO v1.17.1 [48062228] FilePathsBase v0.9.24 [1a297f60] FillArrays v1.15.0 [6a86dc24] FiniteDiff v2.29.0 [53c48c17] FixedPointNumbers v0.8.5 ⌅ [587475ba] Flux v0.14.25 [1fa38f19] Format v1.3.7 [f6369f11] ForwardDiff v1.2.2 ⌅ [d9f16b24] Functors v0.4.12 [0c68f7d7] GPUArrays v11.2.6 [46192b85] GPUArraysCore v0.2.0 [28b8d3ca] GR v0.73.18 [5c1252a2] GeometryBasics v0.5.10 [d7ba0133] Git v1.5.0 [86223c79] Graphs v1.13.1 [42e2da0e] Grisu v1.0.2 [cd3eb016] HTTP v1.10.19 [076d061b] HashArrayMappedTries v0.2.0 [34004b35] HypergeometricFunctions v0.3.28 ⌅ [b5f81e59] IOCapture v0.2.5 [7869d1d1] IRTools v0.4.15 ⌅ [4846b161] InferOpt v0.6.1 [d25df0c9] Inflate v0.1.5 [22cec73e] InitialValues v0.3.1 [842dd82b] InlineStrings v1.4.5 [3587e190] InverseFunctions v0.1.17 [41ab1584] InvertedIndices v1.3.1 [92d709cd] IrrationalConstants v0.2.6 [c8e1da08] IterTools v1.10.0 [b3c1a2ee] IterationControl v0.5.4 [42fd0dbc] IterativeSolvers v0.9.4 [82899510] IteratorInterfaceExtensions v1.0.0 ⌅ [033835bb] JLD2 v0.5.15 [1019f520] JLFzf v0.1.11 [692b3bcd] JLLWrappers v1.7.1 ⌅ [682c06a0] JSON v0.21.4 [b14d175d] JuliaVariables v0.2.4 [63c18a36] KernelAbstractions v0.9.39 [ec8451be] KernelFunctions v0.10.66 [929cbde3] LLVM v9.4.4 [8ac3fa9e] LRUCache v1.6.2 [b964fa9f] LaTeXStrings v1.4.0 [c52c1a26] LaplaceRedux v1.2.0 [23fbe1c1] Latexify v0.16.10 [a5e1c1ea] LatinHypercubeSampling v1.9.0 [0e77f7df] LazilyInitializedFields v1.3.0 ⌅ [92ad9a40] LearnAPI v1.0.1 ⌅ [7acf609c] LightGBM v0.7.2 [d3d80556] LineSearches v7.4.0 [7a12625a] LinearMaps v3.11.4 [70f5e60a] LinkedLists v0.1.1 [2ab3a3ac] LogExpFunctions v0.3.29 [aa2f6b4e] LogarithmicNumbers v1.4.1 [e6f89c97] LoggingExtras v1.2.0 [c2834f40] MLCore v1.0.0 ⌃ [7e8f7934] MLDataDevices v1.5.3 ⌅ [64a0f543] MLFlowClient v0.5.1 ⌅ [add582a8] MLJ v0.20.9 [45f359ea] MLJBalancing v0.1.5 ⌃ [a7f614a8] MLJBase v1.9.2 ⌃ [c6f25543] MLJDecisionTreeInterface v0.4.2 ⌃ [50ed68f4] MLJEnsembles v0.4.3 [7b7b8358] MLJFlow v0.5.0 ⌅ [094fc8d1] MLJFlux v0.5.1 [614be32b] MLJIteration v0.6.4 [6ee0df7b] MLJLinearModels v0.10.1 [e80e1ace] MLJModelInterface v1.12.0 ⌅ [d491faf4] MLJModels v0.17.9 [03970b2e] MLJTuning v0.8.8 [d8e11817] MLStyle v0.4.17 [f1d291b0] MLUtils v0.4.8 [1914dd2f] MacroTools v0.5.16 [d0879d2d] MarkdownAST v0.1.2 [739be429] MbedTLS v1.1.9 [442fdcdd] Measures v0.3.3 [6fafb56a] Memoization v0.2.2 [626554b9] MetaGraphs v0.8.1 [dbeba491] Metalhead v0.9.5 [128add7d] MicroCollections v0.2.0 [e1d29d7a] Missings v1.2.0 [6f286f6a] MultivariateStats v0.10.3 [d41bc354] NLSolversBase v7.10.0 [872c559c] NNlib v0.9.31 [77ba4419] NaNMath v1.1.3 [71a1bf82] NameResolution v0.1.5 [c020b1a1] NaturalSort v1.0.0 [636a865e] NearestNeighborModels v0.2.3 [b8a86587] NearestNeighbors v0.4.22 [46757867] NetworkLayout v0.4.10 [6fe1bfb0] OffsetArrays v1.17.0 [0b1bfda6] OneHotArrays v0.2.10 [8b6db2d4] OpenML v0.3.2 [4d8831e6] OpenSSL v1.6.0 [429524aa] Optim v1.13.2 ⌅ [3bd65402] Optimisers v0.3.4 [bac558e1] OrderedCollections v1.8.1 [90014a1f] PDMats v0.11.36 [65ce6f38] PackageExtensionCompat v1.0.2 [d96e819e] Parameters v0.12.3 [69de0a69] Parsers v2.8.3 [570af359] PartialFunctions v1.2.1 [ccf2f8ad] PlotThemes v3.3.0 [995b91a9] PlotUtils v1.4.4 [91a5bcdd] Plots v1.41.1 [2dfb63ee] PooledArrays v1.4.3 [85a6dd25] PositiveFactorizations v0.2.4 [aea7be01] PrecompileTools v1.3.3 [21216c6a] Preferences v1.5.0 [8162dcfd] PrettyPrint v0.2.0 [54e16d92] PrettyPrinting v0.4.2 ⌅ [08abe8d2] PrettyTables v2.4.0 [33c8b6b6] ProgressLogging v0.1.5 [92933f4c] ProgressMeter v1.11.0 [43287f4e] PtrArrays v1.3.0 [1fd47b50] QuadGK v2.11.2 [c1ae055f] RealDot v0.1.0 [3cdcf5f2] RecipesBase v1.3.4 [01d81517] RecipesPipeline v0.6.12 [189a3867] Reexport v1.2.2 [42d2dcc6] Referenceables v0.1.3 [2792f1a3] RegistryInstances v0.1.0 [05181044] RelocatableFolders v1.0.1 [97f35ef4] RequiredInterfaces v0.1.7 [ae029012] Requires v1.3.1 [79098fc4] Rmath v0.9.0 [321657f4] ScientificTypes v3.1.1 [30f210dd] ScientificTypesBase v3.0.0 [6e75b9c4] ScikitLearnBase v0.5.0 [7e506255] ScopedValues v1.5.0 [6c6a2e73] Scratch v1.3.0 [91c51154] SentinelArrays 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[bc48ee85] Tullio v0.3.8 [5c2747f8] URIs v1.6.1 [3a884ed6] UnPack v1.0.2 [1cfade01] UnicodeFun v0.4.1 [013be700] UnsafeAtomics v0.3.0 [41fe7b60] Unzip v0.2.0 ⌅ [e88e6eb3] Zygote v0.6.77 [700de1a5] ZygoteRules v0.2.7 ⌅ [68821587] Arpack_jll v3.5.1+1 [6e34b625] Bzip2_jll v1.0.9+0 [83423d85] Cairo_jll v1.18.5+0 [ee1fde0b] Dbus_jll v1.16.2+0 [5ae413db] EarCut_jll v2.2.4+0 [2702e6a9] EpollShim_jll v0.0.20230411+1 [2e619515] Expat_jll v2.7.3+0 [b22a6f82] FFMPEG_jll v8.0.0+0 [a3f928ae] Fontconfig_jll v2.17.1+0 [d7e528f0] FreeType2_jll v2.13.4+0 [559328eb] FriBidi_jll v1.0.17+0 [0656b61e] GLFW_jll v3.4.0+2 [d2c73de3] GR_jll v0.73.18+0 [b0724c58] GettextRuntime_jll v0.22.4+0 [61579ee1] Ghostscript_jll v9.55.1+0 [020c3dae] Git_LFS_jll v3.7.0+0 [f8c6e375] Git_jll v2.51.3+0 [7746bdde] Glib_jll v2.86.0+0 [3b182d85] Graphite2_jll v1.3.15+0 [2e76f6c2] HarfBuzz_jll v8.5.1+0 [aacddb02] JpegTurbo_jll v3.1.3+0 [c1c5ebd0] LAME_jll v3.100.3+0 [88015f11] LERC_jll v4.0.1+0 [dad2f222] LLVMExtra_jll v0.0.38+0 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Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. Testing Running tests... WARNING: Method definition _dummy_backedge() in module Memoization at /home/pkgeval/.julia/packages/Memoization/ON3Za/src/Memoization.jl:49 overwritten at /home/pkgeval/.julia/packages/Memoization/ON3Za/src/Memoization.jl:65. ┌ Warning: Unable to determine HTML(edit_link = ...) from remote HEAD branch, defaulting to "master". │ Calling `git remote` failed with an exception. Set JULIA_DEBUG=Documenter to see the error. │ Unless this is due to a configuration error, the relevant variable should be set explicitly. └ @ Documenter ~/.julia/packages/Documenter/HdXI4/src/utilities/utilities.jl:665 [ Info: SetupBuildDirectory: setting up build directory. [ Info: Doctest: running doctests. [ Info: Skipped ExpandTemplates step (doctest only). [ Info: Skipped CrossReferences step (doctest only). [ Info: Skipped CheckDocument step (doctest only). [ Info: Skipped Populate step (doctest only). [ Info: Skipped RenderDocument step (doctest only). Test Summary: | Pass Total Time Doctests: ConformalPrediction | 1 1 47.5s [ Info: For silent loading, specify `verbosity=0`. import NearestNeighborModels ✔ [ Info: Training machine(AdaptiveInductiveClassifier(model = KNNClassifier(K = 5, …), …), …). [ Info: Training machine(AdaptiveInductiveClassifier(model = KNNClassifier(K = 5, …), …), …). [ Info: Training machine(AdaptiveInductiveClassifier(model = KNNClassifier(K = 5, …), …), …). [ Info: Training machine(NaiveClassifier(model = KNNClassifier(K = 5, …), …), …). [ Info: Training machine(NaiveClassifier(model = KNNClassifier(K = 5, …), …), …). [ Info: Training machine(NaiveClassifier(model = KNNClassifier(K = 5, …), …), …). [ Info: Training machine(SimpleInductiveClassifier(model = KNNClassifier(K = 5, …), …), …). [ Info: Training machine(SimpleInductiveClassifier(model = KNNClassifier(K = 5, …), …), …). [ Info: Training machine(SimpleInductiveClassifier(model = KNNClassifier(K = 5, …), …), …). [ Info: For silent loading, specify `verbosity=0`. import EvoTrees ✔ ┌ Info: Training machine(AdaptiveInductiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - tree_type: binary │ - rng: Random.MersenneTwister(123) └ , …), …). ┌ Info: Training machine(AdaptiveInductiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 7014, 6012, 988)) └ , …), …). ┌ Info: Training machine(AdaptiveInductiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 15030, 14028, 272)) └ , …), …). ┌ Info: Training machine(NaiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 22044, 21042, 158)) └ , …), …). ┌ Info: Training machine(NaiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 35070, 34068, 732)) └ , …), …). ┌ Info: Training machine(NaiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 49098, 48096, 604)) └ , …), …). ┌ Info: Training machine(SimpleInductiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 63126, 62124, 76)) └ , …), …). ┌ Info: Training machine(SimpleInductiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 156312, 155310, 887)) └ , …), …). ┌ Info: Training machine(SimpleInductiveClassifier(model = EvoTrees.EvoTreeClassifier{EvoTrees.MLogLoss} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 254508, 253506, 590)) └ , …), …). [ Info: For silent loading, specify `verbosity=0`. import MLJDecisionTreeInterface ✔ [ Info: Training machine(AdaptiveInductiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …). [ Info: Training machine(AdaptiveInductiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …). [ Info: Training machine(AdaptiveInductiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …). [ Info: Training machine(NaiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …). [ Info: Training machine(NaiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …). [ Info: Training machine(NaiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …). [ Info: Training machine(SimpleInductiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …). [ Info: Training machine(SimpleInductiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …). [ Info: Training machine(SimpleInductiveClassifier(model = RandomForestClassifier(max_depth = -1, …), …), …). [ Info: For silent loading, specify `verbosity=0`. import MLJLinearModels ✔ [ Info: Training machine(AdaptiveInductiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: Training machine(AdaptiveInductiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: Training machine(AdaptiveInductiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: Training machine(NaiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: Training machine(NaiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: Training machine(NaiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: Training machine(SimpleInductiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: Training machine(SimpleInductiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: Training machine(SimpleInductiveClassifier(model = LogisticClassifier(lambda = 2.220446049250313e-16, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: For silent loading, specify `verbosity=0`. import MLJDecisionTreeInterface ✔ [ Info: Training machine(AdaptiveInductiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …). [ Info: Training machine(AdaptiveInductiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …). [ Info: Training machine(AdaptiveInductiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …). [ Info: Training machine(NaiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …). [ Info: Training machine(NaiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …). [ Info: Training machine(NaiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …). [ Info: Training machine(SimpleInductiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …). [ Info: Training machine(SimpleInductiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …). [ Info: Training machine(SimpleInductiveClassifier(model = DecisionTreeClassifier(max_depth = -1, …), …), …). [ Info: For silent loading, specify `verbosity=0`. import MLJLinearModels ✔ ┌ Warning: This test is skipped as the method is not suitable for Quantile Regression └ @ Main ~/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:80 [ Info: Training machine(CVPlusRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). [ Info: Training machine(CVPlusRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(NaiveRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). ┌ Info: Solver: MLJLinearModels.Analytical │ iterative: Bool false └ max_inner: Int64 200 [ Info: Training machine(NaiveRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). ┌ Info: Solver: MLJLinearModels.Analytical │ iterative: Bool false └ max_inner: Int64 200 [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). [ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusAbRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). [ Info: Training machine(JackknifePlusAbRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). [ Info: Training machine(JackknifePlusRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(CVMinMaxRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). [ Info: Training machine(CVMinMaxRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifeRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). ┌ Info: Solver: MLJLinearModels.Analytical │ iterative: Bool false └ max_inner: Int64 200 [ Info: Training machine(JackknifeRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). ┌ Info: Solver: MLJLinearModels.Analytical │ iterative: Bool false └ max_inner: Int64 200 [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifeMinMaxRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). [ Info: Training machine(JackknifeMinMaxRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(TimeSeriesRegressorEnsembleBatch(model = RidgeRegressor(lambda = 1.0, …), …), …). [ Info: Training machine(TimeSeriesRegressorEnsembleBatch(model = RidgeRegressor(lambda = 1.0, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(SimpleInductiveRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). ┌ Info: Solver: MLJLinearModels.Analytical │ iterative: Bool false └ max_inner: Int64 200 [ Info: Training machine(SimpleInductiveRegressor(model = RidgeRegressor(lambda = 1.0, …), …), …). ┌ Info: Solver: MLJLinearModels.Analytical │ iterative: Bool false └ max_inner: Int64 200 [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: For silent loading, specify `verbosity=0`. import MLJLinearModels ✔ ┌ Warning: This test is skipped as the method is not suitable for Quantile Regression └ @ Main ~/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:80 [ Info: Training machine(CVPlusRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). [ Info: Training machine(CVPlusRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(NaiveRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). ┌ Info: Solver: MLJLinearModels.ProxGrad │ accel: Bool true │ max_iter: Int64 1000 │ tol: Float64 0.0001 │ max_inner: Int64 100 │ beta: Float64 0.8 └ gram: Bool false [ Info: Training machine(NaiveRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). ┌ Info: Solver: MLJLinearModels.ProxGrad │ accel: Bool true │ max_iter: Int64 1000 │ tol: Float64 0.0001 │ max_inner: Int64 100 │ beta: Float64 0.8 └ gram: Bool false [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). [ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusAbRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). [ Info: Training machine(JackknifePlusAbRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). [ Info: Training machine(JackknifePlusRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(CVMinMaxRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). [ Info: Training machine(CVMinMaxRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifeRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). ┌ Info: Solver: MLJLinearModels.ProxGrad │ accel: Bool true │ max_iter: Int64 1000 │ tol: Float64 0.0001 │ max_inner: Int64 100 │ beta: Float64 0.8 └ gram: Bool false [ Info: Training machine(JackknifeRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). ┌ Info: Solver: MLJLinearModels.ProxGrad │ accel: Bool true │ max_iter: Int64 1000 │ tol: Float64 0.0001 │ max_inner: Int64 100 │ beta: Float64 0.8 └ gram: Bool false [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifeMinMaxRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). [ Info: Training machine(JackknifeMinMaxRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(TimeSeriesRegressorEnsembleBatch(model = LassoRegressor(lambda = 1.0, …), …), …). [ Info: Training machine(TimeSeriesRegressorEnsembleBatch(model = LassoRegressor(lambda = 1.0, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(SimpleInductiveRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). ┌ Info: Solver: MLJLinearModels.ProxGrad │ accel: Bool true │ max_iter: Int64 1000 │ tol: Float64 0.0001 │ max_inner: Int64 100 │ beta: Float64 0.8 └ gram: Bool false [ Info: Training machine(SimpleInductiveRegressor(model = LassoRegressor(lambda = 1.0, …), …), …). ┌ Info: Solver: MLJLinearModels.ProxGrad │ accel: Bool true │ max_iter: Int64 1000 │ tol: Float64 0.0001 │ max_inner: Int64 100 │ beta: Float64 0.8 └ gram: Bool false [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: For silent loading, specify `verbosity=0`. import EvoTrees ✔ ┌ Warning: This test is skipped as the method is not suitable for Quantile Regression └ @ Main ~/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:80 ┌ Info: Training machine(CVPlusRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123) └ , …), …). ┌ Info: Training machine(CVPlusRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 41082, 40080, 521)) └ , …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. ┌ Info: Training machine(NaiveRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 84168, 83166, 435)) └ , …), …). ┌ Info: Training machine(NaiveRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 91182, 90180, 321)) └ , …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. ┌ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 98196, 97194, 607)) └ , …), …). ┌ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 221442, 220440, 365)) └ , …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. ┌ Info: Training machine(JackknifePlusAbRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 356712, 355710, 97)) └ , …), …). ┌ Info: Training machine(JackknifePlusAbRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 478956, 477954, 856)) └ , …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. ┌ Info: Training machine(JackknifePlusRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 614226, 613224, 589)) └ , …), …). ┌ Info: Training machine(JackknifePlusRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 3813612, 3812610, 848)) └ , …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. ┌ Info: Training machine(CVMinMaxRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 7173318, 7172316, 788)) └ , …), …). ┌ Info: Training machine(CVMinMaxRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 7214400, 7213398, 307)) └ , …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. ┌ Info: Training machine(JackknifeRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 7257486, 7256484, 222)) └ , …), …). ┌ Info: Training machine(JackknifeRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 10463886, 10462884, 367)) └ , …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. ┌ Info: Training machine(JackknifeMinMaxRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 13830606, 13829604, 595)) └ , …), …). ┌ Info: Training machine(JackknifeMinMaxRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 17029992, 17028990, 854)) └ , …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. ┌ Info: Training machine(TimeSeriesRegressorEnsembleBatch(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 20389698, 20388696, 793)) └ , …), …). ┌ Info: Training machine(TimeSeriesRegressorEnsembleBatch(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 20530980, 20529978, 512)) └ , …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. ┌ Info: Training machine(SimpleInductiveRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 20692302, 20691300, 194)) └ , …), …). ┌ Info: Training machine(SimpleInductiveRegressor(model = EvoTrees.EvoTreeRegressor{EvoTrees.MSE} │ - nrounds: 100 │ - L2: 0.0 │ - lambda: 0.0 │ - gamma: 0.0 │ - eta: 0.1 │ - max_depth: 6 │ - min_weight: 1.0 │ - rowsample: 1.0 │ - colsample: 1.0 │ - nbins: 64 │ - alpha: 0.5 │ - monotone_constraints: Dict{Int64, Int64}() │ - tree_type: binary │ - rng: Random.MersenneTwister(123, (0, 20740398, 20739396, 696)) └ , …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: For silent loading, specify `verbosity=0`. import NearestNeighborModels ✔ ┌ Warning: This test is skipped as the method is not suitable for Quantile Regression └ @ Main ~/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:80 [ Info: Training machine(CVPlusRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Training machine(CVPlusRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(NaiveRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Training machine(NaiveRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusAbRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Training machine(JackknifePlusAbRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Training machine(JackknifePlusRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(CVMinMaxRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Training machine(CVMinMaxRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifeRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Training machine(JackknifeRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifeMinMaxRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Training machine(JackknifeMinMaxRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(TimeSeriesRegressorEnsembleBatch(model = KNNRegressor(K = 5, …), …), …). [ Info: Training machine(TimeSeriesRegressorEnsembleBatch(model = KNNRegressor(K = 5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(SimpleInductiveRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Training machine(SimpleInductiveRegressor(model = KNNRegressor(K = 5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: For silent loading, specify `verbosity=0`. import MLJDecisionTreeInterface ✔ ┌ Warning: This test is skipped as the method is not suitable for Quantile Regression └ @ Main ~/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:80 [ Info: Training machine(CVPlusRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Training machine(CVPlusRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(NaiveRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Training machine(NaiveRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusAbRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Training machine(JackknifePlusAbRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Training machine(JackknifePlusRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(CVMinMaxRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Training machine(CVMinMaxRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifeRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Training machine(JackknifeRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifeMinMaxRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Training machine(JackknifeMinMaxRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(TimeSeriesRegressorEnsembleBatch(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Training machine(TimeSeriesRegressorEnsembleBatch(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(SimpleInductiveRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Training machine(SimpleInductiveRegressor(model = DecisionTreeRegressor(max_depth = -1, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: For silent loading, specify `verbosity=0`. import MLJLinearModels ✔ [ Info: Training machine(ConformalQuantileRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: Training machine(ConformalQuantileRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(CVPlusRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). [ Info: Training machine(CVPlusRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(NaiveRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: Training machine(NaiveRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). [ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusAbRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). [ Info: Training machine(JackknifePlusAbRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). [ Info: Training machine(JackknifePlusRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(CVMinMaxRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). [ Info: Training machine(CVMinMaxRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifeRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: Training machine(JackknifeRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifeMinMaxRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). [ Info: Training machine(JackknifeMinMaxRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(TimeSeriesRegressorEnsembleBatch(model = QuantileRegressor(delta = 0.5, …), …), …). [ Info: Training machine(TimeSeriesRegressorEnsembleBatch(model = QuantileRegressor(delta = 0.5, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(SimpleInductiveRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: Training machine(SimpleInductiveRegressor(model = QuantileRegressor(delta = 0.5, …), …), …). ┌ Info: Solver: MLJLinearModels.LBFGS{Optim.Options{Float64, Nothing}, @NamedTuple{}} │ optim_options: Optim.Options{Float64, Nothing} └ lbfgs_options: @NamedTuple{} NamedTuple() [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: For silent loading, specify `verbosity=0`. import MLJDecisionTreeInterface ✔ ┌ Warning: This test is skipped as the method is not suitable for Quantile Regression └ @ Main ~/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:80 [ Info: Training machine(CVPlusRegressor(model = RandomForestRegressor(max_depth = -1, …), …), …). [ Info: Training machine(CVPlusRegressor(model = RandomForestRegressor(max_depth = -1, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(NaiveRegressor(model = RandomForestRegressor(max_depth = -1, …), …), …). [ Info: Training machine(NaiveRegressor(model = RandomForestRegressor(max_depth = -1, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = RandomForestRegressor(max_depth = -1, …), …), …). [ Info: Training machine(JackknifePlusAbMinMaxRegressor(model = RandomForestRegressor(max_depth = -1, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusAbRegressor(model = RandomForestRegressor(max_depth = -1, …), …), …). [ Info: Training machine(JackknifePlusAbRegressor(model = RandomForestRegressor(max_depth = -1, …), …), …). [ Info: Multivariate input for regression with no input variable (`input_var`) specified: defaulting to first variable. [ Info: Training machine(JackknifePlusRegressor(model = RandomForestRegressor(max_depth = -1, …), …), …). ====================================================================================== 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 175 running 1 of 1 signal (10): User defined signal 1 Node at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/DecisionTree.jl:60 [inlined] _convert at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/main.jl:9 _convert at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/main.jl:8 _convert at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/main.jl:7 _convert at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/main.jl:7 _convert at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/main.jl:8 _convert at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/main.jl:8 _convert at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/main.jl:8 _convert at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/main.jl:8 _convert at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/main.jl:8 _convert at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/main.jl:7 #build_tree#59 at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/main.jl:65 build_tree at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/main.jl:34 unknown function (ip: 0x7b1d41c1b31b) at (unknown file) _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 macro expansion at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/main.jl:116 [inlined] #65 at ./threadingconstructs.jl:276 #63 at ./threadingconstructs.jl:243 [inlined] #threading_run##0 at ./threadingconstructs.jl:177 unknown function (ip: 0x7b1d41c19bee) at (unknown file) _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 jl_apply at /source/src/julia.h:2284 [inlined] start_task at /source/src/task.c:1272 unknown function (ip: (nil)) at (unknown file) ============================================================== Profile collected. A report will print at the next yield point. Disabling --trace-compile ============================================================== ====================================================================================== 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 uv_run at /workspace/srcdir/libuv/src/unix/core.c:430 ijl_task_get_next at /source/src/scheduler.c:457 wait at ./task.jl:1246 wait_forever at ./task.jl:1168 jfptr_wait_forever_65246.1 at /opt/julia/lib/julia/sys.so (unknown line) _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 jl_apply at /source/src/julia.h:2284 [inlined] start_task at /source/src/task.c:1272 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 0x000076b2566690f0 Total snapshots: 491. Utilization: 0% ╎491 @Base/task.jl:1168 wait_forever() 490╎ 491 @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 Overhead ╎ [+additional indent] Count File:Line Function ========================================================= Thread 1 (default) Task 0x00007b1c715fdc30 Total snapshots: 136. Utilization: 100% ╎136 @Base/…ingconstructs.jl:177 (::Base.Threads.var"#threading_run##0#thre… ╎ 136 @Base/…ingconstructs.jl:243 #63 ╎ 136 @Base/…ngconstructs.jl:276 (::DecisionTree.var"#63#64"{DecisionTree.… ╎ 136 @DecisionTree/…main.jl:116 macro expansion ╎ 136 @DecisionTree/…main.jl:34 kwcall(::@NamedTuple{rng::Random.Xoshiro… ╎ 135 @DecisionTree/…main.jl:53 build_tree(labels::Vector{Float64}, fea… ╎ ╎ 135 @DecisionTree/…ree.jl:294 fit ╎ ╎ 135 @DecisionTree/…ee.jl:321 #fit#1 ╎ ╎ 1 @DecisionTree/…ee.jl:259 _fit(X::Matrix{Float64}, Y::Vector{Fl… ╎ ╎ 1 @Base/boot.jl:666 Array ╎ ╎ 1 @Base/boot.jl:648 Array 1╎ ╎ ╎ 1 @Base/boot.jl:588 GenericMemory ╎ ╎ 116 @DecisionTree/…ee.jl:261 _fit(X::Matrix{Float64}, Y::Vector{Fl… ╎ ╎ 116 @Base/boot.jl:666 Array ╎ ╎ 116 @Base/boot.jl:648 Array 116╎ ╎ ╎ 116 @Base/boot.jl:588 GenericMemory ╎ ╎ 15 @DecisionTree/…ee.jl:269 _fit(X::Matrix{Float64}, Y::Vector{Fl… 1╎ ╎ 1 @DecisionTree/…ee.jl:48 _split!(X::Matrix{Float64}, Y::Vector… ╎ ╎ 1 @DecisionTree/…ee.jl:70 _split!(X::Matrix{Float64}, Y::Vector… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…e.jl:72 macro expansion 1╎ ╎ ╎ 1 @Base/…sentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ee.jl:136 _split!(X::Matrix{Float64}, Y::Vecto… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…e.jl:137 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:963 getindex 1╎ ╎ ╎ 1 @Base/…sentials.jl:965 getindex ╎ ╎ 5 @DecisionTree/…ee.jl:141 _split!(X::Matrix{Float64}, Y::Vecto… 1╎ ╎ 1 @DecisionTree/…l.jl:0 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ 1 @DecisionTree/…l.jl:184 q_bi_sort!(v::Vector{Float64}, w::Ve… ╎ ╎ ╎ 1 @DecisionTree/…l.jl:100 insert_sort!(v::Vector{Float64}, w:… ╎ ╎ ╎ 1 @Base/…sentials.jl:964 getindex 1╎ ╎ ╎ 1 @Base/…sentials.jl:385 checkbounds ╎ ╎ 2 @DecisionTree/…l.jl:190 q_bi_sort!(v::Vector{Float64}, w::Ve… ╎ ╎ ╎ 2 @DecisionTree/…l.jl:184 q_bi_sort!(v::Vector{Float64}, w::V… ╎ ╎ ╎ 1 @DecisionTree/….jl:100 insert_sort!(v::Vector{Float64}, w:… ╎ ╎ ╎ 1 @Base/…sentials.jl:964 getindex 1╎ ╎ ╎ 1 @Base/…sentials.jl:385 checkbounds 1╎ ╎ ╎ 1 @DecisionTree/….jl:103 insert_sort!(v::Vector{Float64}, w:… ╎ ╎ 1 @DecisionTree/…l.jl:193 q_bi_sort!(v::Vector{Float64}, w::Ve… ╎ ╎ ╎ 1 @DecisionTree/…l.jl:193 q_bi_sort!(v::Vector{Float64}, w::V… ╎ ╎ ╎ 1 @DecisionTree/….jl:184 q_bi_sort!(v::Vector{Float64}, w::V… ╎ ╎ ╎ 1 @DecisionTree/….jl:112 insert_sort!(v::Vector{Float64}, w… ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! ╎ ╎ 1 @DecisionTree/…ee.jl:142 _split!(X::Matrix{Float64}, Y::Vecto… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…e.jl:143 macro expansion 1╎ ╎ ╎ 1 @Base/…sentials.jl:965 getindex 1╎ ╎ 1 @DecisionTree/…ee.jl:169 _split!(X::Matrix{Float64}, Y::Vecto… ╎ ╎ 2 @DecisionTree/…ee.jl:181 _split!(X::Matrix{Float64}, Y::Vecto… 1╎ ╎ 1 @Base/simdloop.jl:0 macro expansion ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…e.jl:183 macro expansion 1╎ ╎ ╎ 1 @Base/…sentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ee.jl:218 _split!(X::Matrix{Float64}, Y::Vecto… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…e.jl:219 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:963 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:0 getindex ╎ ╎ 2 @DecisionTree/…ee.jl:233 _split!(X::Matrix{Float64}, Y::Vecto… ╎ ╎ 2 @Base/array.jl:971 getindex ╎ ╎ ╎ 2 @Base/…ractarray.jl:825 similar ╎ ╎ ╎ 2 @Base/…actarray.jl:836 similar ╎ ╎ ╎ 2 @Base/array.jl:407 similar ╎ ╎ ╎ 2 @Base/boot.jl:661 Array ╎ ╎ ╎ 1 @Base/boot.jl:648 Array 1╎ ╎ ╎ ╎ 1 @Base/boot.jl:588 GenericMemory ╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ 3 @DecisionTree/…ee.jl:286 _fit(X::Matrix{Float64}, Y::Vector{Fl… ╎ ╎ 3 @DecisionTree/…ee.jl:243 fork! ╎ ╎ 3 @DecisionTree/…ee.jl:31 NodeMeta 3╎ ╎ ╎ 3 @DecisionTree/…e.jl:31 NodeMeta ╎ 1 @DecisionTree/…main.jl:65 build_tree(labels::Vector{Float64}, fea… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:8 _convert(node::DecisionTree.treereg… ╎ ╎ ╎ 1 @DecisionTree/….jl:7 _convert(node::DecisionTree.treereg… ╎ ╎ ╎ 1 @DecisionTree/….jl:5 _convert(node::DecisionTree.treere… ╎ ╎ ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ ╎ 1 @Base/…tarray.jl:825 similar ╎ ╎ ╎ ╎ 1 @Base/…tarray.jl:836 similar ╎ ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:649 Array Task 0x00007b1c715fdb40 Total snapshots: 29. Utilization: 100% ╎29 @Base/…dingconstructs.jl:177 (::Base.Threads.var"#threading_run##0#thread… ╎ 29 @Base/…dingconstructs.jl:243 #63 ╎ 29 @Base/…dingconstructs.jl:276 (::DecisionTree.var"#63#64"{DecisionTree.v… ╎ 29 @DecisionTree/…/main.jl:116 macro expansion ╎ 29 @DecisionTree/…/main.jl:34 kwcall(::@NamedTuple{rng::Random.Xoshiro, … ╎ 25 @DecisionTree/…/main.jl:53 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 25 @DecisionTree/…tree.jl:294 fit ╎ ╎ 25 @DecisionTree/…tree.jl:321 #fit#1 ╎ ╎ 21 @DecisionTree/…ree.jl:269 _fit(X::Matrix{Float64}, Y::Vector{Floa… 1╎ ╎ 1 @Base/sort.jl:0 _split!(X::Matrix{Float64}, Y::Vector{Float64}, … 1╎ ╎ 1 @DecisionTree/…ree.jl:48 _split!(X::Matrix{Float64}, Y::Vector{F… ╎ ╎ 2 @DecisionTree/…ree.jl:70 _split!(X::Matrix{Float64}, Y::Vector{F… 1╎ ╎ 1 @Base/simdloop.jl:0 macro expansion ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:71 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ree.jl:78 _split!(X::Matrix{Float64}, Y::Vector{F… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:79 macro expansion ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds ╎ ╎ 2 @DecisionTree/…ree.jl:136 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 2 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 2 @DecisionTree/…ee.jl:137 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:963 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! ╎ ╎ 7 @DecisionTree/…ree.jl:141 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Vect… 1╎ ╎ ╎ 1 @DecisionTree/…il.jl:97 insert_sort!(v::Vector{Float64}, w::Ve… ╎ ╎ 3 @DecisionTree/…il.jl:185 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 3 @DecisionTree/…il.jl:161 _bi_partition! ╎ ╎ ╎ 3 @Base/essentials.jl:964 getindex ╎ ╎ ╎ 3 @Base/essentials.jl:385 checkbounds 3╎ ╎ ╎ 3 @Base/essentials.jl:381 checkbounds ╎ ╎ 3 @DecisionTree/…il.jl:190 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 2 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Vec… 1╎ ╎ ╎ 2 @DecisionTree/…il.jl:103 insert_sort!(v::Vector{Float64}, w::… 1╎ ╎ ╎ 1 @Base/float.jl:622 < ╎ ╎ ╎ 1 @DecisionTree/…il.jl:185 q_bi_sort!(v::Vector{Float64}, w::Vec… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:161 _bi_partition! 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ree.jl:142 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:143 macro expansion ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex ╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds 1╎ ╎ ╎ 1 @Base/essentials.jl:381 checkbounds ╎ ╎ 2 @DecisionTree/…ree.jl:158 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/sort.jl:0 searchsortedlast ╎ ╎ 1 @Base/sort.jl:211 searchsortedlast 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ree.jl:181 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/simdloop.jl:75 macro expansion ╎ ╎ 1 @DecisionTree/…ree.jl:218 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:219 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:963 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ree.jl:231 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @DecisionTree/…til.jl:82 partition! ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex ╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds 1╎ ╎ ╎ 1 @Base/essentials.jl:381 checkbounds ╎ ╎ 1 @DecisionTree/…ree.jl:233 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ 1 @Base/…tractarray.jl:825 similar ╎ ╎ ╎ 1 @Base/…tractarray.jl:836 similar ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ 4 @DecisionTree/…ree.jl:286 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 2 @DecisionTree/…ree.jl:242 fork! ╎ ╎ 2 @DecisionTree/…ree.jl:31 NodeMeta 1╎ ╎ ╎ 2 @DecisionTree/…ee.jl:31 NodeMeta ╎ ╎ 2 @DecisionTree/…ree.jl:243 fork! ╎ ╎ 2 @DecisionTree/…ree.jl:31 NodeMeta 2╎ ╎ ╎ 2 @DecisionTree/…ee.jl:31 NodeMeta ╎ 4 @DecisionTree/…/main.jl:65 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 2 @DecisionTree/…/main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 2 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 2 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregresso… ╎ ╎ 2 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:5 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ ╎ 1 @Base/…actarray.jl:825 similar ╎ ╎ ╎ ╎ 1 @Base/…actarray.jl:836 similar ╎ ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ ╎ 1 @Base/boot.jl:661 Array ╎ ╎ ╎ ╎ 1 @Base/boot.jl:648 Array 1╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:588 GenericMemory ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:8 _convert(node::DecisionTree.treeregr… 1╎ ╎ ╎ ╎ 1 @DecisionTree/…n.jl:7 _convert(node::DecisionTree.treereg… ╎ ╎ 2 @DecisionTree/…/main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ ╎ 1 @DecisionTree/…n.jl:8 _convert(node::DecisionTree.treereg… ╎ ╎ ╎ ╎ 1 @DecisionTree/….jl:5 _convert(node::DecisionTree.treereg… ╎ ╎ ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ ╎ 1 @Base/…ctarray.jl:825 similar ╎ ╎ ╎ ╎ 1 @Base/…tarray.jl:836 similar ╎ ╎ ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… 1╎ ╎ ╎ 1 @DecisionTree/…in.jl:5 _convert(node::DecisionTree.treeregre… Task 0x00007b1d67dfc010 Total snapshots: 3. Utilization: 100% ╎3 @Base/client.jl:577 _start() ╎ 3 @Base/client.jl:310 exec_options(opts::Base.JLOptions) ╎ 3 @Base/boot.jl:489 eval(m::Module, e::Any) ╎ 3 @Base/Base.jl:311 (::Base.IncludeInto)(fname::String) ╎ 3 @Base/Base.jl:310 include(mapexpr::Function, mod::Module, _path::Strin… ╎ 3 @Base/loading.jl:3054 _include(mapexpr::Function, mod::Module, _path:… ╎ ╎ 3 @Base/loading.jl:2994 include_string(mapexpr::typeof(identity), mod:… ╎ ╎ 3 @Base/boot.jl:489 eval(m::Module, e::Any) ╎ ╎ 3 @Base/Base.jl:311 (::Base.IncludeInto)(fname::String) ╎ ╎ 3 @Base/Base.jl:310 include(mapexpr::Function, mod::Module, _path::… ╎ ╎ 3 @Base/loading.jl:3054 _include(mapexpr::Function, mod::Module, _… ╎ ╎ ╎ 3 @Base/loading.jl:2994 include_string(mapexpr::typeof(identity),… ╎ ╎ ╎ 3 @Base/boot.jl:489 eval(m::Module, e::Any) ╎ ╎ ╎ 3 …test/regression.jl:23 top-level scope ╎ ╎ ╎ 3 @Test/src/Test.jl:1961 macro expansion ╎ ╎ ╎ 3 …est/regression.jl:26 macro expansion ╎ ╎ ╎ ╎ 3 @Test/src/Test.jl:1961 macro expansion ╎ ╎ ╎ ╎ 3 …st/regression.jl:30 macro expansion ╎ ╎ ╎ ╎ 3 @Test/…rc/Test.jl:1961 macro expansion ╎ ╎ ╎ ╎ 3 …st/regression.jl:39 macro expansion ╎ ╎ ╎ ╎ 3 @Test/…c/Test.jl:1961 macro expansion ╎ ╎ ╎ ╎ ╎ 3 …t/regression.jl:43 macro expansion ╎ ╎ ╎ ╎ ╎ 3 @MLJBase/…nes.jl:787 kwcall(::@NamedTuple{rows::Vect… ╎ ╎ ╎ ╎ ╎ 3 @MLJBase/…nes.jl:790 #fit!#66 ╎ ╎ ╎ ╎ ╎ 3 @MLJBase/…es.jl:617 fit_only! ╎ ╎ ╎ ╎ ╎ 3 @MLJBase/…es.jl:693 fit_only!(mach::Machine{Confo… ╎ ╎ ╎ ╎ ╎ ╎ 1 @ConformalPrediction/…:197 fit(conf_model::Confo… ╎ ╎ ╎ ╎ ╎ ╎ 1 @MLJDecisionTreeInterface/…:340 fit(m::MLJDecis… ╎ ╎ ╎ ╎ ╎ ╎ 1 @DecisionTree/…:76 kwcall(::@NamedTuple{rng::R… ╎ ╎ ╎ ╎ ╎ ╎ 1 @DecisionTree/…:145 build_forest(labels::Vect… ╎ ╎ ╎ ╎ ╎ ╎ 1 @DecisionTree/…:597 _build_forest(forest::Ve… ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @DecisionTree/…:440 impurity_importance ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @DecisionTree/…:441 impurity_importance(tr… ╎ ╎ ╎ ╎ ╎ ╎ 2 @ConformalPrediction/…:204 fit(conf_model::Confo… ╎ ╎ ╎ ╎ ╎ ╎ 2 @MLJDecisionTreeInterface/…:414 predict ╎ ╎ ╎ ╎ ╎ ╎ 2 @DecisionTree/…:634 apply_forest ╎ ╎ ╎ ╎ ╎ ╎ 2 @DecisionTree/…:645 apply_forest(forest::Deci… ╎ ╎ ╎ ╎ ╎ ╎ 2 @DecisionTree/…:615 apply_forest(forest::Dec… 1╎ ╎ ╎ ╎ ╎ ╎ ╎ 2 @DecisionTree/…:281 apply_tree ╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @DecisionTree/…:283 apply_tree(tree::Decis… 1╎ ╎ ╎ ╎ ╎ ╎ ╎ 1 @DecisionTree/…:281 apply_tree(tree::Deci… Task 0x00007b1c715fda50 Total snapshots: 31. Utilization: 100% ╎31 @Base/…dingconstructs.jl:177 (::Base.Threads.var"#threading_run##0#thread… ╎ 31 @Base/…dingconstructs.jl:243 #63 ╎ 31 @Base/…dingconstructs.jl:276 (::DecisionTree.var"#63#64"{DecisionTree.v… 1╎ 31 @DecisionTree/…/main.jl:116 macro expansion ╎ 30 @DecisionTree/…/main.jl:34 kwcall(::@NamedTuple{rng::Random.Xoshiro, … ╎ 26 @DecisionTree/…/main.jl:53 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 26 @DecisionTree/…tree.jl:294 fit ╎ ╎ 26 @DecisionTree/…tree.jl:321 #fit#1 ╎ ╎ 24 @DecisionTree/…ree.jl:269 _fit(X::Matrix{Float64}, Y::Vector{Floa… 3╎ ╎ 3 @Base/sort.jl:0 _split!(X::Matrix{Float64}, Y::Vector{Float64}, … 1╎ ╎ 1 @DecisionTree/…ree.jl:0 _split!(X::Matrix{Float64}, Y::Vector{Fl… ╎ ╎ 1 @DecisionTree/…ree.jl:70 _split!(X::Matrix{Float64}, Y::Vector{F… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:71 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 2 @DecisionTree/…ree.jl:136 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 2 @Base/simdloop.jl:77 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:0 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:137 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! ╎ ╎ 1 @DecisionTree/…ree.jl:141 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @DecisionTree/…il.jl:185 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:169 _bi_partition! ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! ╎ ╎ 2 @DecisionTree/…ree.jl:142 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 2 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:143 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:144 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! ╎ ╎ 4 @DecisionTree/…ree.jl:155 _split!(X::Matrix{Float64}, Y::Vector{… 4╎ ╎ 4 @Base/essentials.jl:965 getindex 1╎ ╎ 1 @DecisionTree/…ree.jl:156 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @DecisionTree/…ree.jl:158 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/sort.jl:211 searchsortedlast ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex ╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds 1╎ ╎ ╎ 1 @Base/essentials.jl:381 checkbounds 1╎ ╎ 1 @DecisionTree/…ree.jl:169 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 3 @DecisionTree/…ree.jl:181 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/simdloop.jl:75 macro expansion ╎ ╎ 2 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 2 @DecisionTree/…ee.jl:182 macro expansion 2╎ ╎ ╎ 2 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ree.jl:188 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/simdloop.jl:75 macro expansion ╎ ╎ 1 @DecisionTree/…ree.jl:218 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:219 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:962 getindex 1╎ ╎ ╎ 1 @Base/…ractarray.jl:702 checkbounds ╎ ╎ 2 @DecisionTree/…ree.jl:233 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 2 @Base/array.jl:971 getindex ╎ ╎ ╎ 2 @Base/…tractarray.jl:825 similar ╎ ╎ ╎ 2 @Base/…tractarray.jl:836 similar ╎ ╎ ╎ 2 @Base/array.jl:407 similar ╎ ╎ ╎ 2 @Base/boot.jl:661 Array ╎ ╎ ╎ 1 @Base/boot.jl:648 Array 1╎ ╎ ╎ ╎ 1 @Base/boot.jl:588 GenericMemory ╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ 2 @DecisionTree/…ree.jl:286 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 2 @DecisionTree/…ree.jl:242 fork! ╎ ╎ 2 @DecisionTree/…ree.jl:31 NodeMeta 2╎ ╎ ╎ 2 @DecisionTree/…ee.jl:31 NodeMeta ╎ 4 @DecisionTree/…/main.jl:65 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 1 @Base/abstractarray.jl:1360 getindex ╎ ╎ 1 @Base/…idimensional.jl:984 _getindex ╎ ╎ 1 @Base/…dimensional.jl:998 _unsafe_getindex ╎ ╎ 1 @Base/…imensional.jl:1007 _unsafe_getindex! ╎ ╎ 1 @Base/cartesian.jl:65 macro expansion 1╎ ╎ ╎ 1 @Base/…imensional.jl:1009 macro expansion ╎ ╎ 3 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregressor.… ╎ ╎ 3 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 3 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregresso… ╎ ╎ 2 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ 2 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:5 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ 1 @Base/…ractarray.jl:825 similar ╎ ╎ ╎ 1 @Base/…ractarray.jl:836 similar ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:5 _convert(node::DecisionTree.treeregre… 1╎ ╎ ╎ 1 @Base/…_compiler.jl:57 getproperty ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:9 _convert(node::DecisionTree.treeregr… 1╎ ╎ ╎ 1 @DecisionTree/…e.jl:60 Node Task 0x00007b1c715fd960 Total snapshots: 36. Utilization: 100% ╎36 @Base/…dingconstructs.jl:177 (::Base.Threads.var"#threading_run##0#thread… ╎ 36 @Base/…dingconstructs.jl:243 #63 ╎ 36 @Base/…dingconstructs.jl:276 (::DecisionTree.var"#63#64"{DecisionTree.v… ╎ 36 @DecisionTree/…/main.jl:116 macro expansion ╎ 36 @DecisionTree/…/main.jl:34 kwcall(::@NamedTuple{rng::Random.Xoshiro, … ╎ 31 @DecisionTree/…/main.jl:53 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 31 @DecisionTree/…tree.jl:294 fit ╎ ╎ 31 @DecisionTree/…tree.jl:321 #fit#1 ╎ ╎ 25 @DecisionTree/…ree.jl:269 _fit(X::Matrix{Float64}, Y::Vector{Floa… 1╎ ╎ 1 @Base/simdloop.jl:0 _split!(X::Matrix{Float64}, Y::Vector{Float6… ╎ ╎ 3 @DecisionTree/…ree.jl:70 _split!(X::Matrix{Float64}, Y::Vector{F… ╎ ╎ 3 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 2 @DecisionTree/…ee.jl:71 macro expansion 2╎ ╎ ╎ 2 @Base/essentials.jl:965 getindex ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:72 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 2 @DecisionTree/…ree.jl:136 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/simdloop.jl:75 macro expansion ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:137 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:963 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex 1╎ ╎ 6 @DecisionTree/…ree.jl:141 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 2 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:0 insert_sort!(v::Vector{Float64}, w::Vec… 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ ╎ 1 @DecisionTree/…il.jl:101 insert_sort!(v::Vector{Float64}, w::V… 1╎ ╎ ╎ 1 @Base/essentials.jl:0 getindex ╎ ╎ 1 @DecisionTree/…il.jl:185 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:152 _bi_partition! ╎ ╎ ╎ 1 @DecisionTree/…il.jl:0 _selectpivot! ╎ ╎ 2 @DecisionTree/…il.jl:193 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 2 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Vec… ╎ ╎ ╎ 2 @DecisionTree/…il.jl:103 insert_sort!(v::Vector{Float64}, w::… 2╎ ╎ ╎ 2 @Base/float.jl:622 < ╎ ╎ 4 @DecisionTree/…ree.jl:142 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 4 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 2 @DecisionTree/…ee.jl:143 macro expansion 2╎ ╎ ╎ 2 @Base/essentials.jl:965 getindex ╎ ╎ ╎ 2 @DecisionTree/…ee.jl:144 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 2 @DecisionTree/…ree.jl:158 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/sort.jl:210 searchsortedlast ╎ ╎ ╎ 1 @Base/array.jl:2257 midpoint 1╎ ╎ ╎ 1 @Base/int.jl:576 >>> ╎ ╎ 1 @Base/sort.jl:211 searchsortedlast ╎ ╎ ╎ 1 @Base/ordering.jl:118 lt ╎ ╎ ╎ 1 @Base/float.jl:639 isless 1╎ ╎ ╎ 1 @Base/int.jl:83 < ╎ ╎ 1 @DecisionTree/…ree.jl:181 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/simdloop.jl:75 macro expansion ╎ ╎ 1 @DecisionTree/…ree.jl:194 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/float.jl:493 - ╎ ╎ 1 @DecisionTree/…ree.jl:211 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/float.jl:494 * ╎ ╎ 1 @DecisionTree/…ree.jl:218 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:219 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:962 getindex ╎ ╎ ╎ 1 @Base/…ractarray.jl:702 checkbounds ╎ ╎ ╎ 1 @Base/…ractarray.jl:684 checkbounds ╎ ╎ ╎ 1 @Base/…actarray.jl:728 checkbounds_indices ╎ ╎ ╎ ╎ 1 @Base/…actarray.jl:757 checkindex 1╎ ╎ ╎ ╎ 1 @Base/int.jl:559 < ╎ ╎ 1 @DecisionTree/…ree.jl:223 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/…se_compiler.jl:61 setproperty! ╎ ╎ 2 @DecisionTree/…ree.jl:233 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ 1 @Base/…tractarray.jl:825 similar ╎ ╎ ╎ 1 @Base/…tractarray.jl:836 similar ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ 1 @Base/array.jl:973 getindex ╎ ╎ ╎ 1 @Base/array.jl:291 copyto! ╎ ╎ ╎ 1 @Base/array.jl:300 _copyto_impl! ╎ ╎ ╎ 1 @Base/…ricmemory.jl:133 unsafe_copyto! 1╎ ╎ ╎ 1 @Base/boot.jl:596 memoryref ╎ ╎ 6 @DecisionTree/…ree.jl:286 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 2 @DecisionTree/…ree.jl:242 fork! ╎ ╎ 2 @DecisionTree/…ree.jl:31 NodeMeta 2╎ ╎ ╎ 2 @DecisionTree/…ee.jl:31 NodeMeta ╎ ╎ 4 @DecisionTree/…ree.jl:243 fork! ╎ ╎ 4 @DecisionTree/…ree.jl:31 NodeMeta 4╎ ╎ ╎ 4 @DecisionTree/…ee.jl:31 NodeMeta ╎ 4 @DecisionTree/…/main.jl:65 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 2 @DecisionTree/…/main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 2 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ ╎ 1 @DecisionTree/…n.jl:8 _convert(node::DecisionTree.treereg… ╎ ╎ ╎ ╎ 1 @DecisionTree/….jl:8 _convert(node::DecisionTree.treereg… ╎ ╎ ╎ ╎ 1 @DecisionTree/….jl:8 _convert(node::DecisionTree.treere… ╎ ╎ ╎ ╎ 1 @DecisionTree/….jl:5 _convert(node::DecisionTree.treer… ╎ ╎ ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ ╎ ╎ 1 @Base/…tarray.jl:825 similar ╎ ╎ ╎ ╎ ╎ 1 @Base/…tarray.jl:836 similar ╎ ╎ ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:5 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ ╎ 1 @Base/…actarray.jl:825 similar ╎ ╎ ╎ ╎ 1 @Base/…actarray.jl:836 similar ╎ ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ 2 @DecisionTree/…/main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 2 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 2 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:7 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ ╎ 1 @DecisionTree/…n.jl:7 _convert(node::DecisionTree.treereg… ╎ ╎ ╎ ╎ 1 @DecisionTree/….jl:7 _convert(node::DecisionTree.treereg… ╎ ╎ ╎ ╎ 1 @DecisionTree/….jl:7 _convert(node::DecisionTree.treere… ╎ ╎ ╎ ╎ 1 @DecisionTree/….jl:7 _convert(node::DecisionTree.treer… ╎ ╎ ╎ ╎ 1 @DecisionTree/…jl:7 _convert(node::DecisionTree.treer… ╎ ╎ ╎ ╎ ╎ 1 @DecisionTree/…jl:5 _convert(node::DecisionTree.tree… ╎ ╎ ╎ ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ ╎ ╎ 1 @Base/…array.jl:825 similar ╎ ╎ ╎ ╎ ╎ 1 @Base/…array.jl:836 similar ╎ ╎ ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:5 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ ╎ 1 @Base/…actarray.jl:825 similar ╎ ╎ ╎ ╎ 1 @Base/…ctarray.jl:836 similar ╎ ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ 1 @DecisionTree/…/main.jl:71 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 1 @DecisionTree/…main.jl:18 update_using_impurity! ╎ ╎ 1 @DecisionTree/…main.jl:17 update_using_impurity!(feature_importanc… ╎ ╎ 1 @DecisionTree/…main.jl:17 update_using_impurity!(feature_importan… ╎ ╎ 1 @DecisionTree/…ain.jl:17 update_using_impurity!(feature_importan… ╎ ╎ 1 @DecisionTree/…ain.jl:18 update_using_impurity!(feature_importa… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:18 update_using_impurity!(feature_importa… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:17 update_using_impurity!(feature_import… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:18 update_using_impurity!(feature_impor… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:18 update_using_impurity!(feature_impor… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:18 update_using_impurity!(feature_impo… ╎ ╎ ╎ ╎ 1 @DecisionTree/….jl:18 update_using_impurity!(feature_impo… 1╎ ╎ ╎ ╎ 1 @Base/array.jl:0 update_using_impurity!(feature_importan… Task 0x00007b1c715fd870 Total snapshots: 30. Utilization: 100% ╎30 @Base/…dingconstructs.jl:177 (::Base.Threads.var"#threading_run##0#thread… ╎ 30 @Base/…dingconstructs.jl:243 #63 ╎ 30 @Base/…dingconstructs.jl:276 (::DecisionTree.var"#63#64"{DecisionTree.v… ╎ 30 @DecisionTree/…/main.jl:116 macro expansion ╎ 30 @DecisionTree/…/main.jl:34 kwcall(::@NamedTuple{rng::Random.Xoshiro, … ╎ 27 @DecisionTree/…/main.jl:53 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 27 @DecisionTree/…tree.jl:294 fit ╎ ╎ 27 @DecisionTree/…tree.jl:321 #fit#1 ╎ ╎ 21 @DecisionTree/…ree.jl:269 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 2 @DecisionTree/…ree.jl:70 _split!(X::Matrix{Float64}, Y::Vector{F… ╎ ╎ 2 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 2 @DecisionTree/…ee.jl:71 macro expansion ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ree.jl:78 _split!(X::Matrix{Float64}, Y::Vector{F… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:79 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ree.jl:87 _split!(X::Matrix{Float64}, Y::Vector{F… ╎ ╎ 1 @Base/operators.jl:424 > 1╎ ╎ ╎ 1 @Base/float.jl:622 < ╎ ╎ 2 @DecisionTree/…ree.jl:136 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 2 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 2 @DecisionTree/…ee.jl:137 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 3 @DecisionTree/…ree.jl:141 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Vect… 1╎ ╎ ╎ 1 @DecisionTree/…il.jl:97 insert_sort!(v::Vector{Float64}, w::Ve… ╎ ╎ 1 @DecisionTree/…il.jl:185 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:161 _bi_partition! 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…il.jl:190 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Vec… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:103 insert_sort!(v::Vector{Float64}, w::… ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds ╎ ╎ 1 @DecisionTree/…ree.jl:142 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:143 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ree.jl:155 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/essentials.jl:965 getindex 2╎ ╎ 2 @DecisionTree/…ree.jl:156 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @DecisionTree/…ree.jl:158 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/sort.jl:0 searchsortedlast ╎ ╎ 1 @DecisionTree/…ree.jl:168 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/float.jl:492 + 1╎ ╎ 1 @DecisionTree/…ree.jl:169 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 2 @DecisionTree/…ree.jl:194 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 2 @Base/float.jl:493 - ╎ ╎ 2 @DecisionTree/…ree.jl:218 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/simdloop.jl:75 macro expansion ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:219 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:963 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ree.jl:233 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ 1 @Base/…tractarray.jl:825 similar ╎ ╎ ╎ 1 @Base/…tractarray.jl:836 similar ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ 5 @DecisionTree/…ree.jl:286 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 1 @DecisionTree/…ree.jl:242 fork! ╎ ╎ 1 @DecisionTree/…ree.jl:31 NodeMeta 1╎ ╎ ╎ 1 @DecisionTree/…ee.jl:31 NodeMeta ╎ ╎ 4 @DecisionTree/…ree.jl:243 fork! ╎ ╎ 4 @DecisionTree/…ree.jl:31 NodeMeta 4╎ ╎ ╎ 4 @DecisionTree/…ee.jl:31 NodeMeta ╎ ╎ 1 @DecisionTree/…ree.jl:288 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 1 @Base/array.jl:1345 push! ╎ ╎ 1 @Base/array.jl:1349 _push! 1╎ ╎ ╎ 1 @Base/array.jl:1044 __safe_setindex! ╎ 3 @DecisionTree/…/main.jl:65 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 1 @DecisionTree/…/main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:7 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ ╎ 1 @DecisionTree/…n.jl:7 _convert(node::DecisionTree.treereg… 1╎ ╎ ╎ ╎ 1 @DecisionTree/….jl:5 _convert(node::DecisionTree.treereg… ╎ ╎ 2 @DecisionTree/…/main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 2 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregressor… 1╎ ╎ 2 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ ╎ 1 @DecisionTree/…n.jl:5 _convert(node::DecisionTree.treereg… ╎ ╎ ╎ ╎ 1 @Base/array.jl:973 getindex ╎ ╎ ╎ ╎ 1 @Base/array.jl:291 copyto! 1╎ ╎ ╎ ╎ 1 @Base/array.jl:298 _copyto_impl! Task 0x00007b1c715fd780 Total snapshots: 31. Utilization: 100% ╎31 @Base/…dingconstructs.jl:177 (::Base.Threads.var"#threading_run##0#thread… ╎ 31 @Base/…dingconstructs.jl:243 #63 ╎ 31 @Base/…dingconstructs.jl:276 (::DecisionTree.var"#63#64"{DecisionTree.v… ╎ 31 @DecisionTree/…/main.jl:116 macro expansion ╎ 2 @Base/abstractarray.jl:1360 getindex ╎ 2 @Base/…idimensional.jl:984 _getindex ╎ ╎ 1 @Base/…idimensional.jl:998 _unsafe_getindex ╎ ╎ 1 @Base/…dimensional.jl:1007 _unsafe_getindex! ╎ ╎ 1 @Base/cartesian.jl:65 macro expansion ╎ ╎ 1 @Base/…imensional.jl:1009 macro expansion ╎ ╎ 1 @Base/essentials.jl:964 getindex ╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds 1╎ ╎ ╎ 1 @Base/essentials.jl:381 checkbounds ╎ ╎ 1 @Base/…idimensional.jl:998 _unsafe_getindex(::IndexLinear, ::Matrix… ╎ ╎ 1 @Base/…dimensional.jl:1007 _unsafe_getindex! ╎ ╎ 1 @Base/cartesian.jl:67 macro expansion ╎ ╎ 1 @Base/…tractarray.jl:1245 iterate ╎ ╎ 1 @Base/…tractarray.jl:1253 _iterate_abstractarray 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ 29 @DecisionTree/…main.jl:34 kwcall(::@NamedTuple{rng::Random.Xoshiro, i… ╎ 25 @DecisionTree/…/main.jl:53 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 25 @DecisionTree/…tree.jl:294 fit ╎ ╎ 25 @DecisionTree/…tree.jl:321 #fit#1 ╎ ╎ 1 @DecisionTree/…ree.jl:259 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 1 @Base/boot.jl:666 Array ╎ ╎ 1 @Base/boot.jl:648 Array 1╎ ╎ ╎ 1 @Base/boot.jl:588 GenericMemory ╎ ╎ 22 @DecisionTree/…ree.jl:269 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 1 @DecisionTree/…ree.jl:70 _split!(X::Matrix{Float64}, Y::Vector{F… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:72 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 3 @DecisionTree/…ree.jl:136 _split!(X::Matrix{Float64}, Y::Vector{… 2╎ ╎ 2 @Base/simdloop.jl:75 macro expansion ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:137 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:963 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 3 @DecisionTree/…ree.jl:141 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @DecisionTree/…il.jl:185 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:161 _bi_partition! ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex ╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds 1╎ ╎ ╎ 1 @Base/essentials.jl:381 checkbounds ╎ ╎ 1 @DecisionTree/…il.jl:190 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Vec… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:102 insert_sort!(v::Vector{Float64}, w::… ╎ ╎ ╎ 1 @Base/operators.jl:424 > 1╎ ╎ ╎ 1 @Base/int.jl:83 < ╎ ╎ 1 @DecisionTree/…il.jl:193 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Vec… 1╎ ╎ ╎ 1 @DecisionTree/…il.jl:0 insert_sort!(v::Vector{Float64}, w::Ve… ╎ ╎ 4 @DecisionTree/…ree.jl:142 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 4 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 2 @DecisionTree/…ee.jl:143 macro expansion ╎ ╎ ╎ 2 @Base/essentials.jl:964 getindex 1╎ ╎ ╎ 2 @Base/essentials.jl:385 checkbounds 1╎ ╎ ╎ 1 @Base/essentials.jl:381 checkbounds 1╎ ╎ ╎ 2 @DecisionTree/…ee.jl:144 macro expansion ╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 2 @DecisionTree/…ree.jl:158 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/sort.jl:0 searchsortedlast ╎ ╎ 1 @Base/sort.jl:211 searchsortedlast ╎ ╎ ╎ 1 @Base/ordering.jl:118 lt 1╎ ╎ ╎ 1 @Base/float.jl:637 isless ╎ ╎ 3 @DecisionTree/…ree.jl:168 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/float.jl:494 * 2╎ ╎ 2 @Base/float.jl:492 + ╎ ╎ 2 @DecisionTree/…ree.jl:169 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 2 @Base/floatfuncs.jl:222 isapprox ╎ ╎ ╎ 2 @Base/floatfuncs.jl:226 #isapprox#714 ╎ ╎ ╎ 2 @Base/float.jl:711 isfinite 2╎ ╎ ╎ 2 @Base/float.jl:493 - ╎ ╎ 2 @DecisionTree/…ree.jl:218 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 2 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 2 @DecisionTree/…ee.jl:219 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:962 getindex 1╎ ╎ ╎ 1 @Base/…ractarray.jl:702 checkbounds ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! ╎ ╎ 2 @DecisionTree/…ree.jl:233 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 2 @Base/array.jl:971 getindex ╎ ╎ ╎ 2 @Base/…tractarray.jl:825 similar ╎ ╎ ╎ 2 @Base/…tractarray.jl:836 similar ╎ ╎ ╎ 2 @Base/array.jl:407 similar ╎ ╎ ╎ 2 @Base/boot.jl:661 Array ╎ ╎ ╎ 2 @Base/boot.jl:648 Array 2╎ ╎ ╎ ╎ 2 @Base/boot.jl:588 GenericMemory ╎ ╎ 2 @DecisionTree/…ree.jl:286 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 1 @DecisionTree/…ree.jl:242 fork! ╎ ╎ 1 @DecisionTree/…ree.jl:31 NodeMeta 1╎ ╎ ╎ 1 @DecisionTree/…ee.jl:31 NodeMeta ╎ ╎ 1 @DecisionTree/…ree.jl:243 fork! ╎ ╎ 1 @DecisionTree/…ree.jl:31 NodeMeta 1╎ ╎ ╎ 1 @DecisionTree/…ee.jl:31 NodeMeta ╎ 4 @DecisionTree/…/main.jl:65 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 3 @DecisionTree/…/main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 3 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 3 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:5 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ ╎ 1 @Base/…actarray.jl:825 similar ╎ ╎ ╎ ╎ 1 @Base/…ctarray.jl:836 similar ╎ ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ ╎ 1 @Base/boot.jl:661 Array ╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:648 Array 1╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:588 GenericMemory ╎ ╎ 2 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ 2 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:5 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ ╎ 1 @Base/…actarray.jl:825 similar ╎ ╎ ╎ ╎ 1 @Base/…ctarray.jl:836 similar ╎ ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:9 _convert(node::DecisionTree.treeregres… 1╎ ╎ ╎ 1 @DecisionTree/…ee.jl:60 Node ╎ ╎ 1 @DecisionTree/…/main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ ╎ 1 @DecisionTree/…n.jl:8 _convert(node::DecisionTree.treereg… ╎ ╎ ╎ ╎ 1 @DecisionTree/….jl:7 _convert(node::DecisionTree.treereg… ╎ ╎ ╎ ╎ 1 @DecisionTree/….jl:5 _convert(node::DecisionTree.treere… ╎ ╎ ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ ╎ 1 @Base/…tarray.jl:825 similar ╎ ╎ ╎ ╎ ╎ 1 @Base/…tarray.jl:836 similar ╎ ╎ ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:649 Array Task 0x00007b1c715fd690 Total snapshots: 32. Utilization: 100% ╎32 @Base/…dingconstructs.jl:177 (::Base.Threads.var"#threading_run##0#thread… ╎ 32 @Base/…dingconstructs.jl:243 #63 ╎ 32 @Base/…dingconstructs.jl:276 (::DecisionTree.var"#63#64"{DecisionTree.v… ╎ 32 @DecisionTree/…/main.jl:116 macro expansion ╎ 1 @Base/abstractarray.jl:1360 getindex ╎ 1 @Base/…idimensional.jl:984 _getindex ╎ ╎ 1 @Base/…idimensional.jl:996 _unsafe_getindex ╎ ╎ 1 @Base/abstractarray.jl:825 similar ╎ ╎ 1 @Base/…stractarray.jl:836 similar ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ 1 @Base/boot.jl:661 Array ╎ ╎ ╎ 1 @Base/boot.jl:648 Array 1╎ ╎ ╎ 1 @Base/boot.jl:588 GenericMemory ╎ 31 @DecisionTree/…main.jl:34 kwcall(::@NamedTuple{rng::Random.Xoshiro, i… ╎ 27 @DecisionTree/…/main.jl:53 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 27 @DecisionTree/…tree.jl:294 fit ╎ ╎ 27 @DecisionTree/…tree.jl:321 #fit#1 ╎ ╎ 1 @DecisionTree/…ree.jl:264 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 1 @Base/range.jl:1408 collect ╎ ╎ 1 @Base/boot.jl:675 Array ╎ ╎ ╎ 1 @Base/range.jl:1400 Array 1╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ 21 @DecisionTree/…ree.jl:269 _fit(X::Matrix{Float64}, Y::Vector{Floa… 1╎ ╎ 1 @DecisionTree/…ree.jl:0 _split!(X::Matrix{Float64}, Y::Vector{Fl… ╎ ╎ 6 @DecisionTree/…ree.jl:70 _split!(X::Matrix{Float64}, Y::Vector{F… 2╎ ╎ 2 @Base/simdloop.jl:75 macro expansion ╎ ╎ 4 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 2 @DecisionTree/…ee.jl:71 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ ╎ 2 @DecisionTree/…ee.jl:72 macro expansion ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex ╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds 1╎ ╎ ╎ 1 @Base/essentials.jl:381 checkbounds 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 4 @DecisionTree/…ree.jl:141 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:103 insert_sort!(v::Vector{Float64}, w::V… ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds ╎ ╎ 1 @DecisionTree/…il.jl:185 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:166 _bi_partition! ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds ╎ ╎ 2 @DecisionTree/…il.jl:190 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:185 q_bi_sort!(v::Vector{Float64}, w::Vec… 1╎ ╎ ╎ 1 @DecisionTree/…il.jl:158 _bi_partition! ╎ ╎ ╎ 1 @DecisionTree/…il.jl:193 q_bi_sort!(v::Vector{Float64}, w::Vec… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:190 q_bi_sort!(v::Vector{Float64}, w::Ve… ╎ ╎ ╎ 1 @DecisionTree/…l.jl:184 q_bi_sort!(v::Vector{Float64}, w::Ve… 1╎ ╎ ╎ 1 @DecisionTree/…l.jl:113 insert_sort!(v::Vector{Float64}, w:… ╎ ╎ 1 @DecisionTree/…ree.jl:142 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:143 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 3 @DecisionTree/…ree.jl:158 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/sort.jl:209 searchsortedlast 1╎ ╎ ╎ 1 @Base/int.jl:86 - ╎ ╎ 2 @Base/sort.jl:211 searchsortedlast 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ ╎ 1 @Base/ordering.jl:118 lt ╎ ╎ ╎ 1 @Base/float.jl:637 isless ╎ ╎ ╎ 1 @Base/float.jl:708 isnan ╎ ╎ ╎ 1 @Base/operators.jl:320 != 1╎ ╎ ╎ 1 @Base/float.jl:621 == ╎ ╎ 1 @DecisionTree/…ree.jl:168 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/float.jl:492 + ╎ ╎ 1 @DecisionTree/…ree.jl:169 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/floatfuncs.jl:222 isapprox 1╎ ╎ ╎ 1 @Base/floatfuncs.jl:0 #isapprox#714 ╎ ╎ 2 @DecisionTree/…ree.jl:181 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/simdloop.jl:69 macro expansion ╎ ╎ ╎ 1 @Base/range.jl:5 Colon ╎ ╎ ╎ 1 @Base/range.jl:417 UnitRange 1╎ ╎ ╎ 1 @Base/range.jl:428 unitrange_last ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:183 macro expansion 1╎ ╎ ╎ 1 @Base/float.jl:494 * ╎ ╎ 1 @DecisionTree/…ree.jl:231 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @DecisionTree/…til.jl:79 partition! ╎ ╎ 1 @DecisionTree/…ree.jl:233 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ 1 @Base/…tractarray.jl:825 similar ╎ ╎ ╎ 1 @Base/…tractarray.jl:836 similar ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ 1 @Base/boot.jl:661 Array ╎ ╎ ╎ 1 @Base/boot.jl:648 Array 1╎ ╎ ╎ ╎ 1 @Base/boot.jl:588 GenericMemory ╎ ╎ 4 @DecisionTree/…ree.jl:286 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 4 @DecisionTree/…ree.jl:242 fork! ╎ ╎ 4 @DecisionTree/…ree.jl:31 NodeMeta 4╎ ╎ ╎ 4 @DecisionTree/…ee.jl:31 NodeMeta ╎ ╎ 1 @DecisionTree/…ree.jl:0 _split!(X::Matrix{Float64}, Y::Vector{Flo… ╎ 3 @DecisionTree/…/main.jl:65 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 2 @DecisionTree/…/main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 2 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:8 _convert(node::DecisionTree.treeregr… 1╎ ╎ ╎ ╎ 1 @DecisionTree/…n.jl:3 _convert(node::DecisionTree.treereg… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:5 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ ╎ 1 @Base/…actarray.jl:825 similar ╎ ╎ ╎ ╎ 1 @Base/…actarray.jl:836 similar ╎ ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ 1 @DecisionTree/…/main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… 1╎ ╎ ╎ 1 @DecisionTree/…in.jl:5 _convert(node::DecisionTree.treeregre… ╎ 1 @DecisionTree/…/main.jl:71 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 1 @DecisionTree/…main.jl:17 update_using_impurity! ╎ ╎ 1 @DecisionTree/…main.jl:17 update_using_impurity!(feature_importanc… ╎ ╎ 1 @DecisionTree/…main.jl:18 update_using_impurity!(feature_importan… ╎ ╎ 1 @DecisionTree/…ain.jl:17 update_using_impurity!(feature_importan… ╎ ╎ 1 @DecisionTree/…ain.jl:18 update_using_impurity!(feature_importa… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:18 update_using_impurity!(feature_importa… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:19 update_using_impurity!(feature_import… 1╎ ╎ ╎ 1 @Base/float.jl:493 - Task 0x00007b1c715fd5a0 Total snapshots: 32. Utilization: 100% ╎31 @Base/…dingconstructs.jl:177 (::Base.Threads.var"#threading_run##0#thread… ╎ 31 @Base/…dingconstructs.jl:243 #63 ╎ 31 @Base/…dingconstructs.jl:276 (::DecisionTree.var"#63#64"{DecisionTree.v… ╎ 1 @DecisionTree/…/main.jl:114 macro expansion ╎ 1 @Random/src/RNGs.jl:242 seed! ╎ 1 @Random/…rc/Xoshiro.jl:246 seed! ╎ ╎ 1 @Random/src/Random.jl:265 rand ╎ ╎ 1 @Random/…generation.jl:187 rand(rng::Random.SeedHasher, sp::Random… ╎ ╎ 1 @Base/ntuple.jl:65 ntuple ╎ ╎ 1 @Base/ntuple.jl:68 macro expansion ╎ ╎ 1 @Random/…neration.jl:187 #rand##0 ╎ ╎ ╎ 1 @Random/src/RNGs.jl:168 rand ╎ ╎ ╎ 1 @Random/…c/Random.jl:265 rand 1╎ ╎ ╎ 1 @Random/…rc/RNGs.jl:159 rand 1╎ 30 @DecisionTree/…/main.jl:116 macro expansion ╎ 1 @Base/abstractarray.jl:1360 getindex ╎ 1 @Base/…idimensional.jl:984 _getindex ╎ ╎ 1 @Base/…idimensional.jl:996 _unsafe_getindex ╎ ╎ 1 @Base/abstractarray.jl:825 similar ╎ ╎ 1 @Base/…stractarray.jl:836 similar ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ 1 @Base/boot.jl:661 Array ╎ ╎ ╎ 1 @Base/boot.jl:648 Array 1╎ ╎ ╎ 1 @Base/boot.jl:588 GenericMemory ╎ 28 @DecisionTree/…main.jl:34 kwcall(::@NamedTuple{rng::Random.Xoshiro, i… ╎ 24 @DecisionTree/…/main.jl:53 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 24 @DecisionTree/…tree.jl:294 fit ╎ ╎ 24 @DecisionTree/…tree.jl:321 #fit#1 ╎ ╎ 22 @DecisionTree/…ree.jl:269 _fit(X::Matrix{Float64}, Y::Vector{Floa… 1╎ ╎ 1 @Base/sort.jl:0 _split!(X::Matrix{Float64}, Y::Vector{Float64}, … 1╎ ╎ 1 @DecisionTree/…ree.jl:0 _split!(X::Matrix{Float64}, Y::Vector{Fl… ╎ ╎ 1 @DecisionTree/…ree.jl:70 _split!(X::Matrix{Float64}, Y::Vector{F… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:71 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ree.jl:78 _split!(X::Matrix{Float64}, Y::Vector{F… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:81 macro expansion 1╎ ╎ ╎ 1 @Base/float.jl:492 + ╎ ╎ 1 @DecisionTree/…ree.jl:127 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/essentials.jl:964 getindex ╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds ╎ ╎ ╎ 1 @Base/essentials.jl:381 checkbounds ╎ ╎ ╎ 1 @Base/essentials.jl:11 length 1╎ ╎ ╎ 1 @Base/essentials.jl:10 size ╎ ╎ 1 @DecisionTree/…ree.jl:128 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ree.jl:136 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:137 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:963 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex 1╎ ╎ 5 @DecisionTree/…ree.jl:141 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:98 insert_sort!(v::Vector{Float64}, w::Ve… 1╎ ╎ ╎ 1 @Base/int.jl:87 + ╎ ╎ 1 @DecisionTree/…il.jl:185 q_bi_sort!(v::Vector{Float64}, w::Vect… 1╎ ╎ ╎ 1 @DecisionTree/…il.jl:158 _bi_partition! ╎ ╎ 2 @DecisionTree/…il.jl:190 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Vec… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:111 insert_sort!(v::Vector{Float64}, w::… ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! ╎ ╎ ╎ 1 @Base/array.jl:1024 _setindex! 1╎ ╎ ╎ 1 @Base/essentials.jl:0 checkbounds ╎ ╎ ╎ 1 @DecisionTree/…il.jl:190 q_bi_sort!(v::Vector{Float64}, w::Vec… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Ve… ╎ ╎ ╎ 1 @DecisionTree/…l.jl:113 insert_sort!(v::Vector{Float64}, w::… 1╎ ╎ ╎ 1 @Base/range.jl:925 iterate ╎ ╎ 3 @DecisionTree/…ree.jl:142 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/simdloop.jl:0 macro expansion ╎ ╎ 2 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:143 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:144 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex 1╎ ╎ 1 @DecisionTree/…ree.jl:156 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @DecisionTree/…ree.jl:158 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/sort.jl:0 searchsortedlast ╎ ╎ 1 @DecisionTree/…ree.jl:168 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/float.jl:492 + 1╎ ╎ 1 @DecisionTree/…ree.jl:169 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @DecisionTree/…ree.jl:181 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/simdloop.jl:75 macro expansion ╎ ╎ 1 @DecisionTree/…ree.jl:218 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:219 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:963 getindex ╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ree.jl:233 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ 1 @Base/…tractarray.jl:825 similar ╎ ╎ ╎ 1 @Base/…tractarray.jl:836 similar ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ 1 @Base/boot.jl:661 Array ╎ ╎ ╎ 1 @Base/boot.jl:648 Array 1╎ ╎ ╎ ╎ 1 @Base/boot.jl:588 GenericMemory ╎ ╎ 2 @DecisionTree/…ree.jl:286 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 2 @DecisionTree/…ree.jl:242 fork! ╎ ╎ 2 @DecisionTree/…ree.jl:31 NodeMeta 2╎ ╎ ╎ 2 @DecisionTree/…ee.jl:31 NodeMeta ╎ 4 @DecisionTree/…/main.jl:65 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 1 @DecisionTree/…/main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… 1╎ ╎ ╎ 1 @DecisionTree/…in.jl:3 _convert(node::DecisionTree.treeregres… ╎ ╎ 3 @DecisionTree/…/main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 3 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregre… 1╎ ╎ ╎ 1 @DecisionTree/…in.jl:5 _convert(node::DecisionTree.treeregr… ╎ ╎ 2 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregresso… ╎ ╎ 2 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:5 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ ╎ 1 @Base/array.jl:973 getindex ╎ ╎ ╎ ╎ 1 @Base/array.jl:291 copyto! ╎ ╎ ╎ ╎ 1 @Base/array.jl:300 _copyto_impl! ╎ ╎ ╎ ╎ 1 @Base/…cmemory.jl:139 unsafe_copyto! 1╎ ╎ ╎ ╎ 1 @Base/cmem.jl:28 memmove ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… 1╎ ╎ ╎ 1 @DecisionTree/…in.jl:9 _convert(node::DecisionTree.treeregres… Task 0x00007b1c715fd4b0 Total snapshots: 32. Utilization: 100% ╎32 @Base/…dingconstructs.jl:177 (::Base.Threads.var"#threading_run##0#thread… ╎ 32 @Base/…dingconstructs.jl:243 #63 ╎ 32 @Base/…dingconstructs.jl:276 (::DecisionTree.var"#63#64"{DecisionTree.v… ╎ 32 @DecisionTree/…/main.jl:116 macro expansion ╎ 32 @DecisionTree/…/main.jl:34 kwcall(::@NamedTuple{rng::Random.Xoshiro, … ╎ 29 @DecisionTree/…/main.jl:53 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 29 @DecisionTree/…tree.jl:294 fit ╎ ╎ 29 @DecisionTree/…tree.jl:321 #fit#1 ╎ ╎ 24 @DecisionTree/…ree.jl:269 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 3 @DecisionTree/…ree.jl:70 _split!(X::Matrix{Float64}, Y::Vector{F… 1╎ ╎ 1 @Base/simdloop.jl:75 macro expansion ╎ ╎ 2 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 2 @DecisionTree/…ee.jl:71 macro expansion ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex ╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds 1╎ ╎ ╎ 1 @Base/essentials.jl:381 checkbounds 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ree.jl:84 _split!(X::Matrix{Float64}, Y::Vector{F… ╎ ╎ 1 @Base/…se_compiler.jl:61 setproperty! 1╎ ╎ 1 @DecisionTree/…ree.jl:121 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @DecisionTree/…ree.jl:136 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:137 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! ╎ ╎ 5 @DecisionTree/…ree.jl:141 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 2 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Vect… 1╎ ╎ ╎ 1 @DecisionTree/…il.jl:0 insert_sort!(v::Vector{Float64}, w::Vec… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:100 insert_sort!(v::Vector{Float64}, w::V… ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds ╎ ╎ 1 @DecisionTree/…il.jl:185 q_bi_sort!(v::Vector{Float64}, w::Vect… 1╎ ╎ ╎ 1 @DecisionTree/…il.jl:158 _bi_partition! ╎ ╎ 2 @DecisionTree/…il.jl:190 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:190 q_bi_sort!(v::Vector{Float64}, w::Vec… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Ve… 1╎ ╎ ╎ 1 @DecisionTree/…il.jl:0 insert_sort!(v::Vector{Float64}, w::V… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:193 q_bi_sort!(v::Vector{Float64}, w::Vec… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Ve… 1╎ ╎ ╎ 1 @DecisionTree/…l.jl:103 insert_sort!(v::Vector{Float64}, w::… ╎ ╎ 3 @DecisionTree/…ree.jl:142 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 3 @Base/simdloop.jl:77 macro expansion 1╎ ╎ ╎ 2 @DecisionTree/…ee.jl:143 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:144 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ree.jl:155 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/essentials.jl:965 getindex 2╎ ╎ 2 @DecisionTree/…ree.jl:156 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 2 @DecisionTree/…ree.jl:158 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 2 @Base/sort.jl:211 searchsortedlast ╎ ╎ ╎ 2 @Base/ordering.jl:118 lt ╎ ╎ ╎ 1 @Base/float.jl:637 isless ╎ ╎ ╎ 1 @Base/float.jl:708 isnan ╎ ╎ ╎ 1 @Base/operators.jl:320 != 1╎ ╎ ╎ 1 @Base/float.jl:621 == ╎ ╎ ╎ 1 @Base/float.jl:639 isless ╎ ╎ ╎ 1 @Base/float.jl:631 _fpint 1╎ ╎ ╎ 1 @Base/essentials.jl:778 reinterpret ╎ ╎ 2 @DecisionTree/…ree.jl:168 _split!(X::Matrix{Float64}, Y::Vector{… 2╎ ╎ 2 @Base/float.jl:492 + ╎ ╎ 1 @DecisionTree/…ree.jl:181 _split!(X::Matrix{Float64}, Y::Vector{… 1╎ ╎ 1 @Base/simdloop.jl:0 macro expansion ╎ ╎ 2 @DecisionTree/…ree.jl:231 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 2 @DecisionTree/…til.jl:82 partition! ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex ╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds 1╎ ╎ ╎ 1 @Base/essentials.jl:381 checkbounds ╎ ╎ ╎ 1 @Base/operators.jl:424 > 1╎ ╎ ╎ 1 @Base/float.jl:622 < ╎ ╎ 4 @DecisionTree/…ree.jl:286 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 4 @DecisionTree/…ree.jl:243 fork! ╎ ╎ 4 @DecisionTree/…ree.jl:31 NodeMeta 4╎ ╎ ╎ 4 @DecisionTree/…ee.jl:31 NodeMeta 1╎ ╎ 1 @DecisionTree/…ree.jl:48 _split!(X::Matrix{Float64}, Y::Vector{Fl… ╎ 2 @DecisionTree/…/main.jl:65 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 2 @DecisionTree/…/main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 2 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 2 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:9 _convert(node::DecisionTree.treeregres… 1╎ ╎ ╎ 1 @DecisionTree/…ee.jl:60 Node ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:7 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ ╎ 1 @DecisionTree/…n.jl:5 _convert(node::DecisionTree.treereg… ╎ ╎ ╎ ╎ 1 @Base/array.jl:973 getindex ╎ ╎ ╎ ╎ 1 @Base/array.jl:291 copyto! ╎ ╎ ╎ ╎ 1 @Base/array.jl:298 _copyto_impl! 1╎ ╎ ╎ ╎ 1 @Base/boot.jl:596 memoryref ╎ 1 @DecisionTree/…/main.jl:71 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 1 @DecisionTree/…main.jl:17 update_using_impurity! ╎ ╎ 1 @DecisionTree/…main.jl:18 update_using_impurity!(feature_importanc… ╎ ╎ 1 @DecisionTree/…main.jl:18 update_using_impurity!(feature_importan… ╎ ╎ 1 @DecisionTree/…ain.jl:18 update_using_impurity!(feature_importan… ╎ ╎ 1 @DecisionTree/…ain.jl:18 update_using_impurity!(feature_importa… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:17 update_using_impurity!(feature_importa… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:18 update_using_impurity!(feature_import… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:17 update_using_impurity!(feature_impor… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:17 update_using_impurity!(feature_impor… 1╎ ╎ ╎ 1 @Base/array.jl:0 update_using_impurity!(feature_importance… Task 0x00007b1c715fd3c0 Total snapshots: 33. Utilization: 100% ╎33 @Base/…dingconstructs.jl:177 (::Base.Threads.var"#threading_run##0#thread… ╎ 33 @Base/…dingconstructs.jl:243 #63 ╎ 33 @Base/…dingconstructs.jl:276 (::DecisionTree.var"#63#64"{DecisionTree.v… ╎ 33 @DecisionTree/…/main.jl:116 macro expansion ╎ 33 @DecisionTree/…/main.jl:34 kwcall(::@NamedTuple{rng::Random.Xoshiro, … ╎ 30 @DecisionTree/…/main.jl:53 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 30 @DecisionTree/…tree.jl:294 fit ╎ ╎ 30 @DecisionTree/…tree.jl:321 #fit#1 ╎ ╎ 26 @DecisionTree/…ree.jl:269 _fit(X::Matrix{Float64}, Y::Vector{Floa… 1╎ ╎ 1 @Base/array.jl:0 _split!(X::Matrix{Float64}, Y::Vector{Float64},… 1╎ ╎ 1 @DecisionTree/…ree.jl:0 _split!(X::Matrix{Float64}, Y::Vector{Fl… 2╎ ╎ 2 @DecisionTree/…ree.jl:48 _split!(X::Matrix{Float64}, Y::Vector{F… ╎ ╎ 2 @DecisionTree/…ree.jl:70 _split!(X::Matrix{Float64}, Y::Vector{F… ╎ ╎ 2 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 2 @DecisionTree/…ee.jl:71 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex 1╎ ╎ 1 @DecisionTree/…ree.jl:121 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 8 @DecisionTree/…ree.jl:141 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 4 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 3 @DecisionTree/…il.jl:101 insert_sort!(v::Vector{Float64}, w::V… 1╎ ╎ ╎ 1 @Base/essentials.jl:0 getindex 2╎ ╎ ╎ 2 @Base/essentials.jl:965 getindex 1╎ ╎ ╎ 1 @DecisionTree/…il.jl:103 insert_sort!(v::Vector{Float64}, w::V… ╎ ╎ 2 @DecisionTree/…il.jl:185 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:152 _bi_partition! ╎ ╎ ╎ 1 @DecisionTree/…il.jl:141 _selectpivot! ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! ╎ ╎ ╎ 1 @DecisionTree/…il.jl:168 _bi_partition! ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! ╎ ╎ 2 @DecisionTree/…il.jl:193 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Vec… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:103 insert_sort!(v::Vector{Float64}, w::… 1╎ ╎ ╎ 1 @Base/float.jl:622 < ╎ ╎ ╎ 1 @DecisionTree/…il.jl:193 q_bi_sort!(v::Vector{Float64}, w::Vec… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Ve… ╎ ╎ ╎ 1 @DecisionTree/…l.jl:103 insert_sort!(v::Vector{Float64}, w::… ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex 1╎ ╎ ╎ 1 @Base/…sentials.jl:385 checkbounds ╎ ╎ 3 @DecisionTree/…ree.jl:142 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 3 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:143 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! ╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! ╎ ╎ ╎ 2 @DecisionTree/…ee.jl:144 macro expansion ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ree.jl:158 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/sort.jl:211 searchsortedlast ╎ ╎ ╎ 1 @Base/ordering.jl:118 lt ╎ ╎ ╎ 1 @Base/float.jl:637 isless ╎ ╎ ╎ 1 @Base/float.jl:708 isnan ╎ ╎ ╎ 1 @Base/operators.jl:320 != 1╎ ╎ ╎ 1 @Base/float.jl:621 == ╎ ╎ 1 @DecisionTree/…ree.jl:181 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:182 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 2 @DecisionTree/…ree.jl:218 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 2 @Base/simdloop.jl:77 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:0 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:219 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:963 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 4 @DecisionTree/…ree.jl:233 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 4 @Base/array.jl:971 getindex ╎ ╎ ╎ 4 @Base/…tractarray.jl:825 similar ╎ ╎ ╎ 4 @Base/…tractarray.jl:836 similar ╎ ╎ ╎ 4 @Base/array.jl:407 similar ╎ ╎ ╎ 4 @Base/boot.jl:661 Array ╎ ╎ ╎ 1 @Base/boot.jl:648 Array 1╎ ╎ ╎ ╎ 1 @Base/boot.jl:588 GenericMemory 3╎ ╎ ╎ 3 @Base/boot.jl:649 Array ╎ ╎ 4 @DecisionTree/…ree.jl:286 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 3 @DecisionTree/…ree.jl:242 fork! ╎ ╎ 3 @DecisionTree/…ree.jl:31 NodeMeta 3╎ ╎ ╎ 3 @DecisionTree/…ee.jl:31 NodeMeta ╎ ╎ 1 @DecisionTree/…ree.jl:243 fork! ╎ ╎ 1 @DecisionTree/…ree.jl:31 NodeMeta 1╎ ╎ ╎ 1 @DecisionTree/…ee.jl:31 NodeMeta ╎ 3 @DecisionTree/…/main.jl:65 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 3 @DecisionTree/…/main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(no [175] signal 15: Terminated in expression starting at /home/pkgeval/.julia/packages/ConformalPrediction/bz1ka/test/regression.jl:22 _split! at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/tree.jl:156 _fit at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/tree.jl:269 #fit#1 at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/tree.jl:321 [inlined] fit at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/tree.jl:294 [inlined] #build_tree#59 at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/main.jl:53 build_tree at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/main.jl:34 unknown function (ip: 0x7b1d41c1b31b) at (unknown file) _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 macro expansion at /home/pkgeval/.julia/packages/DecisionTree/0Dw1P/src/regression/main.jl:116 [inlined] #65 at ./threadingconstructs.jl:276 #63 at ./threadingconstructs.jl:243 [inlined] #threading_run##0 at ./threadingconstructs.jl:177 unknown function (ip: 0x7b1d41c19bee) at (unknown file) _jl_invoke at /source/src/gf.c:4116 [inlined] ijl_apply_generic at /source/src/gf.c:4313 jl_apply at /source/src/julia.h:2284 [inlined] start_task at /source/src/task.c:1272 unknown function (ip: (nil)) at (unknown file) Allocations: 1118841156 (Pool: 1118835537; Big: 5619); GC: 340 de::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… 1╎ ╎ ╎ 1 @DecisionTree/…in.jl:5 _convert(node::DecisionTree.treeregre… ╎ ╎ 2 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:7 _convert(node::DecisionTree.treeregr… 1╎ ╎ ╎ ╎ 1 @DecisionTree/…n.jl:5 _convert(node::DecisionTree.treereg… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:9 _convert(node::DecisionTree.treeregre… 1╎ ╎ ╎ 1 @DecisionTree/…e.jl:60 Node Task 0x00007b1c715fd2d0 Total snapshots: 25. Utilization: 100% ╎25 @Base/…dingconstructs.jl:177 (::Base.Threads.var"#threading_run##0#thread… ╎ 25 @Base/…dingconstructs.jl:243 #63 ╎ 25 @Base/…dingconstructs.jl:276 (::DecisionTree.var"#63#64"{DecisionTree.v… ╎ 25 @DecisionTree/…/main.jl:116 macro expansion ╎ 1 @Base/abstractarray.jl:1360 getindex ╎ 1 @Base/…idimensional.jl:984 _getindex ╎ ╎ 1 @Base/…idimensional.jl:998 _unsafe_getindex(::IndexLinear, ::Matrix… ╎ ╎ 1 @Base/…dimensional.jl:1007 _unsafe_getindex! ╎ ╎ 1 @Base/cartesian.jl:67 macro expansion ╎ ╎ 1 @Base/…tractarray.jl:1245 iterate ╎ ╎ 1 @Base/…tractarray.jl:1253 _iterate_abstractarray 1╎ ╎ ╎ 1 @Base/int.jl:87 + ╎ 24 @DecisionTree/…main.jl:34 kwcall(::@NamedTuple{rng::Random.Xoshiro, i… ╎ 19 @DecisionTree/…/main.jl:53 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 19 @DecisionTree/…tree.jl:294 fit ╎ ╎ 19 @DecisionTree/…tree.jl:321 #fit#1 ╎ ╎ 16 @DecisionTree/…ree.jl:269 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 4 @DecisionTree/…ree.jl:70 _split!(X::Matrix{Float64}, Y::Vector{F… 1╎ ╎ 1 @Base/simdloop.jl:0 macro expansion ╎ ╎ 3 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 3 @DecisionTree/…ee.jl:71 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! 1╎ ╎ ╎ 1 @Base/essentials.jl:0 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex 1╎ ╎ 1 @DecisionTree/…ree.jl:124 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @DecisionTree/…ree.jl:136 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:137 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:963 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 2 @DecisionTree/…ree.jl:141 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:100 insert_sort!(v::Vector{Float64}, w::V… 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…il.jl:185 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:161 _bi_partition! ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex ╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds 1╎ ╎ ╎ 1 @Base/essentials.jl:381 checkbounds ╎ ╎ 3 @DecisionTree/…ree.jl:142 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/simdloop.jl:0 macro expansion ╎ ╎ 2 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:143 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:144 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex 2╎ ╎ 2 @DecisionTree/…ree.jl:169 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @DecisionTree/…ree.jl:181 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:182 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 1 @DecisionTree/…ree.jl:231 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @DecisionTree/…til.jl:82 partition! ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex ╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds 1╎ ╎ ╎ 1 @Base/essentials.jl:381 checkbounds ╎ ╎ 1 @DecisionTree/…ree.jl:233 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ 1 @Base/…tractarray.jl:825 similar ╎ ╎ ╎ 1 @Base/…tractarray.jl:836 similar ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ 3 @DecisionTree/…ree.jl:286 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 1 @DecisionTree/…ree.jl:242 fork! ╎ ╎ 1 @DecisionTree/…ree.jl:31 NodeMeta 1╎ ╎ ╎ 1 @DecisionTree/…ee.jl:31 NodeMeta ╎ ╎ 2 @DecisionTree/…ree.jl:243 fork! ╎ ╎ 2 @DecisionTree/…ree.jl:31 NodeMeta 2╎ ╎ ╎ 2 @DecisionTree/…ee.jl:31 NodeMeta ╎ 4 @DecisionTree/…/main.jl:65 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 3 @DecisionTree/…/main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 3 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 3 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregresso… ╎ ╎ 3 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:5 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ ╎ 1 @Base/…actarray.jl:825 similar ╎ ╎ ╎ ╎ 1 @Base/…ctarray.jl:836 similar ╎ ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ 2 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 2 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:8 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ ╎ 1 @DecisionTree/…n.jl:5 _convert(node::DecisionTree.treereg… ╎ ╎ ╎ ╎ 1 @Base/array.jl:973 getindex ╎ ╎ ╎ ╎ 1 @Base/array.jl:291 copyto! ╎ ╎ ╎ ╎ 1 @Base/array.jl:300 _copyto_impl! ╎ ╎ ╎ ╎ 1 @Base/…memory.jl:139 unsafe_copyto! 1╎ ╎ ╎ ╎ ╎ 1 @Base/cmem.jl:28 memmove ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:9 _convert(node::DecisionTree.treeregre… 1╎ ╎ ╎ 1 @DecisionTree/…e.jl:60 Node ╎ ╎ 1 @DecisionTree/…/main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:5 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ ╎ 1 @Base/array.jl:973 getindex ╎ ╎ ╎ ╎ 1 @Base/array.jl:291 copyto! ╎ ╎ ╎ ╎ 1 @Base/array.jl:298 _copyto_impl! 1╎ ╎ ╎ ╎ 1 @Base/boot.jl:596 memoryref ╎ 1 @DecisionTree/…/main.jl:71 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 1 @DecisionTree/…main.jl:17 update_using_impurity! ╎ ╎ 1 @DecisionTree/…main.jl:18 update_using_impurity!(feature_importanc… ╎ ╎ 1 @DecisionTree/…main.jl:17 update_using_impurity!(feature_importan… ╎ ╎ 1 @DecisionTree/…ain.jl:17 update_using_impurity!(feature_importan… ╎ ╎ 1 @DecisionTree/…ain.jl:17 update_using_impurity!(feature_importa… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:19 update_using_impurity!(feature_importa… ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! Task 0x00007b1c715fd1e0 Total snapshots: 35. Utilization: 100% ╎35 @Base/…dingconstructs.jl:177 (::Base.Threads.var"#threading_run##0#thread… ╎ 35 @Base/…dingconstructs.jl:243 #63 ╎ 35 @Base/…dingconstructs.jl:276 (::DecisionTree.var"#63#64"{DecisionTree.v… ╎ 35 @DecisionTree/…/main.jl:116 macro expansion ╎ 35 @DecisionTree/…/main.jl:34 kwcall(::@NamedTuple{rng::Random.Xoshiro, … ╎ 33 @DecisionTree/…/main.jl:53 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 33 @DecisionTree/…tree.jl:294 fit ╎ ╎ 33 @DecisionTree/…tree.jl:321 #fit#1 ╎ ╎ 25 @DecisionTree/…ree.jl:269 _fit(X::Matrix{Float64}, Y::Vector{Floa… 1╎ ╎ 1 @DecisionTree/…ree.jl:0 _split!(X::Matrix{Float64}, Y::Vector{Fl… ╎ ╎ 4 @DecisionTree/…ree.jl:70 _split!(X::Matrix{Float64}, Y::Vector{F… ╎ ╎ 4 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:71 macro expansion 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ ╎ 3 @DecisionTree/…ee.jl:72 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! 1╎ ╎ ╎ 2 @Base/essentials.jl:965 getindex ╎ ╎ 2 @DecisionTree/…ree.jl:136 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 2 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 2 @DecisionTree/…ee.jl:137 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:963 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex 1╎ ╎ 7 @DecisionTree/…ree.jl:141 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 3 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 2 @DecisionTree/…il.jl:100 insert_sort!(v::Vector{Float64}, w::V… 2╎ ╎ ╎ 2 @Base/essentials.jl:965 getindex ╎ ╎ ╎ 1 @DecisionTree/…il.jl:103 insert_sort!(v::Vector{Float64}, w::V… ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex 1╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds ╎ ╎ 3 @DecisionTree/…il.jl:190 q_bi_sort!(v::Vector{Float64}, w::Vect… ╎ ╎ ╎ 2 @DecisionTree/…il.jl:190 q_bi_sort!(v::Vector{Float64}, w::Vec… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Ve… ╎ ╎ ╎ 1 @DecisionTree/…l.jl:101 insert_sort!(v::Vector{Float64}, w::… 1╎ ╎ ╎ 1 @Base/essentials.jl:0 getindex ╎ ╎ ╎ 1 @DecisionTree/…il.jl:185 q_bi_sort!(v::Vector{Float64}, w::Ve… ╎ ╎ ╎ 1 @DecisionTree/…l.jl:161 _bi_partition! ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex ╎ ╎ ╎ 1 @Base/…sentials.jl:385 checkbounds 1╎ ╎ ╎ ╎ 1 @Base/…sentials.jl:381 checkbounds ╎ ╎ ╎ 1 @DecisionTree/…il.jl:193 q_bi_sort!(v::Vector{Float64}, w::Vec… ╎ ╎ ╎ 1 @DecisionTree/…il.jl:184 q_bi_sort!(v::Vector{Float64}, w::Ve… ╎ ╎ ╎ 1 @DecisionTree/…l.jl:102 insert_sort!(v::Vector{Float64}, w::… ╎ ╎ ╎ 1 @Base/operators.jl:424 > 1╎ ╎ ╎ 1 @Base/int.jl:83 < ╎ ╎ 4 @DecisionTree/…ree.jl:142 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/simdloop.jl:75 macro expansion 1╎ ╎ ╎ 1 @Base/int.jl:83 < ╎ ╎ 3 @Base/simdloop.jl:77 macro expansion 1╎ ╎ ╎ 2 @DecisionTree/…ee.jl:143 macro expansion ╎ ╎ ╎ 1 @Base/essentials.jl:964 getindex ╎ ╎ ╎ 1 @Base/essentials.jl:385 checkbounds 1╎ ╎ ╎ 1 @Base/essentials.jl:381 checkbounds ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:144 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:1020 setindex! 1╎ ╎ ╎ 1 @Base/array.jl:1025 _setindex! ╎ ╎ 1 @DecisionTree/…ree.jl:158 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/sort.jl:211 searchsortedlast 1╎ ╎ ╎ 1 @Base/essentials.jl:965 getindex ╎ ╎ 3 @DecisionTree/…ree.jl:168 _split!(X::Matrix{Float64}, Y::Vector{… 3╎ ╎ 3 @Base/float.jl:492 + ╎ ╎ 1 @DecisionTree/…ree.jl:218 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/simdloop.jl:77 macro expansion ╎ ╎ ╎ 1 @DecisionTree/…ee.jl:219 macro expansion ╎ ╎ ╎ 1 @Base/array.jl:962 getindex 1╎ ╎ ╎ 1 @Base/…ractarray.jl:702 checkbounds ╎ ╎ 2 @DecisionTree/…ree.jl:233 _split!(X::Matrix{Float64}, Y::Vector{… ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ 1 @Base/…tractarray.jl:825 similar ╎ ╎ ╎ 1 @Base/…tractarray.jl:836 similar ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ 1 @Base/array.jl:973 getindex ╎ ╎ ╎ 1 @Base/array.jl:291 copyto! ╎ ╎ ╎ 1 @Base/array.jl:300 _copyto_impl! ╎ ╎ ╎ 1 @Base/…ricmemory.jl:133 unsafe_copyto! 1╎ ╎ ╎ 1 @Base/boot.jl:596 memoryref ╎ ╎ 8 @DecisionTree/…ree.jl:286 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 5 @DecisionTree/…ree.jl:242 fork! ╎ ╎ 5 @DecisionTree/…ree.jl:31 NodeMeta 5╎ ╎ ╎ 5 @DecisionTree/…ee.jl:31 NodeMeta ╎ ╎ 3 @DecisionTree/…ree.jl:243 fork! ╎ ╎ 3 @DecisionTree/…ree.jl:31 NodeMeta 3╎ ╎ ╎ 3 @DecisionTree/…ee.jl:31 NodeMeta ╎ 2 @DecisionTree/…/main.jl:65 build_tree(labels::Vector{Float64}, featu… ╎ ╎ 2 @DecisionTree/…/main.jl:8 _convert(node::DecisionTree.treeregressor… ╎ ╎ 2 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregressor… ╎ ╎ 2 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregresso… ╎ ╎ 1 @DecisionTree/…main.jl:7 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:7 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ 1 @DecisionTree/…n.jl:7 _convert(node::DecisionTree.treeregr… ╎ ╎ ╎ ╎ 1 @DecisionTree/…n.jl:7 _convert(node::DecisionTree.treereg… ╎ ╎ ╎ ╎ 1 @DecisionTree/….jl:7 _convert(node::DecisionTree.treereg… ╎ ╎ ╎ ╎ 1 @DecisionTree/….jl:8 _convert(node::DecisionTree.treere… ╎ ╎ ╎ ╎ 1 @DecisionTree/….jl:5 _convert(node::DecisionTree.treer… ╎ ╎ ╎ ╎ 1 @Base/array.jl:971 getindex ╎ ╎ ╎ ╎ ╎ 1 @Base/…tarray.jl:825 similar ╎ ╎ ╎ ╎ ╎ 1 @Base/…tarray.jl:836 similar ╎ ╎ ╎ ╎ ╎ 1 @Base/array.jl:407 similar ╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:661 Array 1╎ ╎ ╎ ╎ ╎ 1 @Base/boot.jl:649 Array ╎ ╎ 1 @DecisionTree/…main.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregress… ╎ ╎ ╎ 1 @DecisionTree/…ain.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregres… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:8 _convert(node::DecisionTree.treeregre… ╎ ╎ ╎ 1 @DecisionTree/…in.jl:9 _convert(node::DecisionTree.treeregr… 1╎ ╎ ╎ 1 @DecisionTree/…e.jl:60 Node Task 0x00007b1c715fd0f0 Total snapshots: 3. Utilization: 100% ╎3 @Base/…adingconstructs.jl:177 (::Base.Threads.var"#threading_run##0#thread… ╎ 3 @Base/…dingconstructs.jl:243 #63 ╎ 3 @Base/…dingconstructs.jl:276 (::DecisionTree.var"#63#64"{DecisionTree.va… ╎ 3 @DecisionTree/…n/main.jl:116 macro expansion ╎ 3 @DecisionTree/…n/main.jl:34 kwcall(::@NamedTuple{rng::Random.Xoshiro, … ╎ 3 @DecisionTree/…/main.jl:53 build_tree(labels::Vector{Float64}, featur… ╎ ╎ 3 @DecisionTree/…tree.jl:294 fit ╎ ╎ 3 @DecisionTree/…tree.jl:321 #fit#1 ╎ ╎ 1 @DecisionTree/…tree.jl:268 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 1 @Base/array.jl:1674 pop! ╎ ╎ 1 @Base/array.jl:1288 _deleteend! ╎ ╎ ╎ 1 @Base/array.jl:211 _unsetindex! ╎ ╎ ╎ 1 @Base/…ericmemory.jl:106 _unsetindex! ╎ ╎ 1 @DecisionTree/…tree.jl:269 _fit(X::Matrix{Float64}, Y::Vector{Floa… 1╎ ╎ 1 @DecisionTree/…ree.jl:169 _split!(X::Matrix{Float64}, Y::Vector{F… ╎ ╎ 1 @DecisionTree/…tree.jl:286 _fit(X::Matrix{Float64}, Y::Vector{Floa… ╎ ╎ 1 @DecisionTree/…ree.jl:242 fork! ╎ ╎ 1 @DecisionTree/…ree.jl:31 NodeMeta 1╎ ╎ ╎ 1 @DecisionTree/…ree.jl:31 NodeMeta PkgEval terminated after 2725.82s: test duration exceeded the time limit