Package evaluation to test ModalDecisionTrees on Julia 1.14.0-DEV.2435 (e1b2c72e96*) started at 2026-06-26T01:48:41.952


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

Installing PkgEval dependencies (TestEnv)...
  Activating project at `~/.julia/environments/v1.14`

Set-up completed after 14.6s


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

Installing ModalDecisionTrees...
   Resolving package versions...
    Updating `~/.julia/environments/v1.14/Project.toml`
  [e54bda2e] + ModalDecisionTrees v0.5.3
    Updating `~/.julia/environments/v1.14/Manifest.toml`
  [da404889] + ARFFFiles v1.6.0
  [1520ce14] + AbstractTrees v0.4.5
  [66dad0bd] + AliasTables v1.1.3
  [ec485272] + ArnoldiMethod v0.4.0
  [d1d4a3ce] + BitFlags v0.1.10
  [336ed68f] + CSV v0.10.16
  [acdeb78f] + Catch22 v0.7.0
  [324d7699] + CategoricalArrays v1.1.1
  [af321ab8] + CategoricalDistributions v0.2.2
  [da1fd8a2] + CodeTracking v3.0.2
  [944b1d66] + CodecZlib v0.7.8
  [3da002f7] + ColorTypes v0.12.1
  [861a8166] + Combinatorics v1.1.0
  [34da2185] + Compat v4.18.1
  [807dbc54] + Compiler v0.1.1
  [f0e56b4a] + ConcurrentUtilities v2.5.1
  [187b0558] + ConstructionBase v1.6.0
  [a8cc5b0e] + Crayons v4.1.1
  [9a962f9c] + DataAPI v1.16.0
  [a93c6f00] + DataFrames v1.8.2
⌅ [864edb3b] + DataStructures v0.18.22
  [e2d170a0] + DataValueInterfaces v1.0.0
  [e7dc6d0d] + DataValues v0.4.13
  [8bb1440f] + DelimitedFiles v1.9.1
  [85a47980] + Dictionaries v0.4.6
⌅ [0703355e] + DimensionalData v0.29.27
  [6e83dbb3] + Discretizers v3.2.4
  [31c24e10] + Distributions v0.25.127
  [ffbed154] + DocStringExtensions v0.9.5
  [460bff9d] + ExceptionUnwrapping v0.1.11
  [411431e0] + Extents v0.1.6
  [48062228] + FilePathsBase v0.9.24
  [1a297f60] + FillArrays v1.16.0
⌅ [53c48c17] + FixedPointNumbers v0.8.6
  [069b7b12] + FunctionWrappers v1.1.3
⌃ [86223c79] + Graphs v1.13.1
⌅ [cd3eb016] + HTTP v1.11.0
  [34004b35] + HypergeometricFunctions v0.3.28
  [313cdc1a] + Indexing v1.1.1
  [d25df0c9] + Inflate v0.1.5
  [842dd82b] + InlineStrings v1.4.5
  [85a1e053] + Interfaces v0.3.2
  [8197267c] + IntervalSets v0.7.14
  [41ab1584] + InvertedIndices v1.3.1
  [92d709cd] + IrrationalConstants v0.2.6
  [c8e1da08] + IterTools v1.10.0
  [1c8ee90f] + IterableTables v1.0.0
  [82899510] + IteratorInterfaceExtensions v1.0.0
  [692b3bcd] + JLLWrappers v1.8.0
  [682c06a0] + JSON v1.6.1
⌅ [aa1ae85d] + JuliaInterpreter v0.10.12
  [b964fa9f] + LaTeXStrings v1.4.0
  [50d2b5c4] + Lazy v0.15.1
  [2ab3a3ac] + LogExpFunctions v1.0.1
  [e6f89c97] + LoggingExtras v1.2.0
⌃ [6f1432cf] + LoweredCodeUtils v3.6.2
  [e80e1ace] + MLJModelInterface v1.12.1
  [1914dd2f] + MacroTools v0.5.16
  [739be429] + MbedTLS v1.1.10
  [6fafb56a] + Memoization v0.2.2
  [e1d29d7a] + Missings v1.2.0
  [e54bda2e] + ModalDecisionTrees v0.5.3
  [8cc5100c] + MultiData v0.1.4
  [8b6db2d4] + OpenML v0.3.3
  [4d8831e6] + OpenSSL v1.6.1
⌅ [bac558e1] + OrderedCollections v1.8.2
  [90014a1f] + PDMats v0.11.38
  [69de0a69] + Parsers v2.8.6
  [2dfb63ee] + PooledArrays v1.4.3
  [aea7be01] + PrecompileTools v1.3.4
  [21216c6a] + Preferences v1.5.2
  [08abe8d2] + PrettyTables v3.3.2
  [33c8b6b6] + ProgressLogging v0.1.6
  [92933f4c] + ProgressMeter v1.11.0
  [43287f4e] + PtrArrays v1.4.0
  [1fd47b50] + QuadGK v2.11.3
  [1a8c2f83] + Query v1.1.0
  [2aef5ad7] + QueryOperators v1.0.1
  [189a3867] + Reexport v1.2.2
  [ae029012] + Requires v1.3.1
  [c5292f4c] + ResumableFunctions v1.0.6
  [295af30f] + Revise v3.15.1
  [79098fc4] + Rmath v0.9.0
  [321657f4] + ScientificTypes v3.3.0
  [30f210dd] + ScientificTypesBase v3.1.0
  [6c6a2e73] + Scratch v1.3.0
  [91c51154] + SentinelArrays v1.4.10
  [777ac1f9] + SimpleBufferStream v1.2.0
  [699a6c99] + SimpleTraits v0.9.6
  [4475fa32] + SoleBase v0.13.4
  [123f1ae1] + SoleData v0.16.8
  [b002da8f] + SoleLogics v0.13.7
  [4249d9c7] + SoleModels v0.10.7
  [a2af1166] + SortingAlgorithms v1.2.3
  [276daf66] + SpecialFunctions v2.8.0
  [90137ffa] + StaticArrays v1.9.18
  [1e83bf80] + StaticArraysCore v1.4.4
  [64bff920] + StatisticalTraits v3.5.0
  [10745b16] + Statistics v1.11.1
  [82ae8749] + StatsAPI v1.8.0
  [2913bbd2] + StatsBase v0.34.12
  [4c63d2b9] + StatsFuns v2.2.0
  [892a3eda] + StringManipulation v0.4.4
  [ec057cc2] + StructUtils v2.8.2
  [5e66a065] + TableShowUtils v0.2.7
  [3783bdb8] + TableTraits v1.0.1
  [382cd787] + TableTraitsUtils v1.0.2
  [bd369af6] + Tables v1.12.1
  [4239201d] + ThreadSafeDicts v0.1.6
⌅ [f3112013] + TimeseriesFeatures v0.6.1
  [3bb67fe8] + TranscodingStreams v0.11.3
  [5c2747f8] + URIs v1.6.1
  [2fbcfb34] + UniqueVectors v1.2.0
  [ea10d353] + WeakRefStrings v1.4.3
  [76eceee3] + WorkerUtilities v1.6.1
  [a5390f91] + ZipFile v0.10.1
  [c8ffd9c3] + MbedTLS_jll v2.28.1010+0
  [efe28fd5] + OpenSpecFun_jll v0.5.6+0
  [f50d1b31] + Rmath_jll v0.5.1+0
  [8a07c0c5] + catch22_jll v0.5.0+0
  [0dad84c5] + ArgTools v1.2.0
  [56f22d72] + Artifacts v1.11.0
  [2a0f44e3] + Base64 v1.11.0
  [8bf52ea8] + CRC32c v1.11.0
  [ade2ca70] + Dates v1.11.0
  [8ba89e20] + Distributed v1.11.0
  [f43a241f] + Downloads v1.7.0
  [7b1f6079] + FileWatching v1.11.0
  [9fa8497b] + Future v1.11.0
  [b77e0a4c] + InteractiveUtils v1.11.0
  [ac6e5ff7] + JuliaSyntaxHighlighting v1.13.0
  [4af54fe1] + LazyArtifacts v1.11.0
  [b27032c2] + LibCURL v1.0.0
  [76f85450] + LibGit2 v1.11.0
  [8f399da3] + Libdl v1.11.0
  [37e2e46d] + LinearAlgebra v1.14.0
  [56ddb016] + Logging v1.11.0
  [d6f4376e] + Markdown v1.11.0
  [a63ad114] + Mmap v1.11.0
  [ca575930] + NetworkOptions v1.3.0
  [44cfe95a] + Pkg v1.14.0
  [de0858da] + Printf v1.11.0
  [3fa0cd96] + REPL v1.11.0
  [9a3f8284] + Random v1.11.0
  [ea8e919c] + SHA v1.13.0
  [9e88b42a] + Serialization v1.11.0
  [1a1011a3] + SharedArrays v1.11.0
  [6462fe0b] + Sockets v1.11.0
  [2f01184e] + SparseArrays v1.13.0
  [f489334b] + StyledStrings v1.13.0
  [4607b0f0] + SuiteSparse
  [fa267f1f] + TOML v1.0.3
  [a4e569a6] + Tar v1.10.0
  [8dfed614] + Test v1.11.0
  [cf7118a7] + UUIDs v1.11.0
  [4ec0a83e] + Unicode v1.11.0
  [e66e0078] + CompilerSupportLibraries_jll v1.5.5+0
  [deac9b47] + LibCURL_jll v8.20.0+1
  [e37daf67] + LibGit2_jll v1.9.4+0
  [29816b5a] + LibSSH2_jll v1.11.101+0
  [14a3606d] + MozillaCACerts_jll v2026.5.14
  [4536629a] + OpenBLAS_jll v0.3.33+0
  [05823500] + OpenLibm_jll v0.8.7+0
  [458c3c95] + OpenSSL_jll v3.5.7+0
  [efcefdf7] + PCRE2_jll v10.47.0+0
  [bea87d4a] + SuiteSparse_jll v7.10.1+0
  [83775a58] + Zlib_jll v1.3.2+0
  [3161d3a3] + Zstd_jll v1.5.7+1
  [8e850b90] + libblastrampoline_jll v5.15.0+0
  [8e850ede] + nghttp2_jll v1.69.0+0
  [3f19e933] + p7zip_jll v17.8.0+0
        Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m`

Installation completed after 6.07s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...
Precompiling project...
  26.9 s  ✓ ImageCorners
  18.0 s  ✓ ImageSegmentation
  15.5 s  ✓ MLJTuning
  51.5 s  ✓ ModalDecisionTrees
  24.5 s  ✓ MLDatasets
  25.4 s  ✓ Images
  24.1 s  ✓ MLJ
  7 dependencies successfully precompiled in 193 seconds. 453 already precompiled.

Precompilation completed after 225.92s


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

     Testing ModalDecisionTrees
      Status `/tmp/jl_witLO9/Project.toml`
  [da404889] ARFFFiles v1.6.0
  [1520ce14] AbstractTrees v0.4.5
  [324d7699] CategoricalArrays v1.1.1
  [af321ab8] CategoricalDistributions v0.2.2
  [e3df1716] D3Trees v0.3.8
  [a93c6f00] DataFrames v1.8.2
⌅ [864edb3b] DataStructures v0.18.22
  [31c24e10] Distributions v0.25.127
  [1a297f60] FillArrays v1.16.0
  [069b7b12] FunctionWrappers v1.1.3
⌅ [cd3eb016] HTTP v1.11.0
  [6a3955dd] ImageFiltering v0.7.12
  [916415d5] Images v0.26.2
  [50d2b5c4] Lazy v0.15.1
  [eb30cadb] MLDatasets v0.7.21
  [add582a8] MLJ v0.23.2
  [a7f614a8] MLJBase v1.13.1
  [e80e1ace] MLJModelInterface v1.12.1
  [6fafb56a] Memoization v0.2.2
  [e54bda2e] ModalDecisionTrees v0.5.3
  [8cc5100c] MultiData v0.1.4
  [8b6db2d4] OpenML v0.3.3
  [7f904dfe] PlutoUI v0.7.83
  [92933f4c] ProgressMeter v1.11.0
  [ce6b1742] RDatasets v0.8.1
  [189a3867] Reexport v1.2.2
  [c5292f4c] ResumableFunctions v1.0.6
  [321657f4] ScientificTypes v3.3.0
  [4475fa32] SoleBase v0.13.4
  [123f1ae1] SoleData v0.16.8
  [b002da8f] SoleLogics v0.13.7
  [4249d9c7] SoleModels v0.10.7
  [2913bbd2] StatsBase v0.34.12
  [bd369af6] Tables v1.12.1
  [a5390f91] ZipFile v0.10.1
  [b77e0a4c] InteractiveUtils v1.11.0
  [37e2e46d] LinearAlgebra v1.14.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [de0858da] Printf v1.11.0
  [9a3f8284] Random v1.11.0
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_witLO9/Manifest.toml`
  [da404889] ARFFFiles v1.6.0
  [621f4979] AbstractFFTs v1.5.0
  [6e696c72] AbstractPlutoDingetjes v1.4.0
  [1520ce14] AbstractTrees v0.4.5
  [79e6a3ab] Adapt v4.7.0
  [66dad0bd] AliasTables v1.1.3
  [ec485272] ArnoldiMethod v0.4.0
  [4fba245c] ArrayInterface v7.25.0
  [a9b6321e] Atomix v1.1.3
  [a963bdd2] AtomsBase v0.5.2
  [13072b0f] AxisAlgorithms v1.1.0
  [39de3d68] AxisArrays v0.4.8
  [ab4f0b2a] BFloat16s v0.6.1
  [50ba71b6] BitBasis v0.9.10
  [d1d4a3ce] BitFlags v0.1.10
  [62783981] BitTwiddlingConvenienceFunctions v0.1.6
  [fa961155] CEnum v0.5.0
  [2a0fbf3d] CPUSummary v0.2.7
  [336ed68f] CSV v0.10.16
  [49dc2e85] Calculus v0.5.2
  [aafaddc9] CatIndices v0.2.2
  [acdeb78f] Catch22 v0.7.0
  [324d7699] CategoricalArrays v1.1.1
  [af321ab8] CategoricalDistributions v0.2.2
  [d360d2e6] ChainRulesCore v1.26.1
  [46823bd8] Chemfiles v0.10.43
  [0b6fb165] ChunkCodecCore v1.0.1
  [4c0bbee4] ChunkCodecLibZlib v1.0.0
  [55437552] ChunkCodecLibZstd v1.0.0
  [fb6a15b2] CloseOpenIntervals v0.1.13
  [aaaa29a8] Clustering v0.15.8
  [da1fd8a2] CodeTracking v3.0.2
  [944b1d66] CodecZlib v0.7.8
  [6b39b394] CodecZstd v0.8.7
  [35d6a980] ColorSchemes v3.31.0
  [3da002f7] ColorTypes v0.12.1
  [c3611d14] ColorVectorSpace v0.11.0
  [5ae59095] Colors v0.13.1
  [861a8166] Combinatorics v1.1.0
  [f70d9fcc] CommonWorldInvalidations v1.1.0
  [34da2185] Compat v4.18.1
  [807dbc54] Compiler v0.1.1
  [ed09eef8] ComputationalResources v0.3.2
  [f0e56b4a] ConcurrentUtilities v2.5.1
  [187b0558] ConstructionBase v1.6.0
  [150eb455] CoordinateTransformations v0.6.4
  [adafc99b] CpuId v0.3.1
  [a8cc5b0e] Crayons v4.1.1
  [dc8bdbbb] CustomUnitRanges v1.0.2
  [e3df1716] D3Trees v0.3.8
  [9a962f9c] DataAPI v1.16.0
  [124859b0] DataDeps v0.7.14
  [a93c6f00] DataFrames v1.8.2
⌅ [864edb3b] DataStructures v0.18.22
  [e2d170a0] DataValueInterfaces v1.0.0
  [e7dc6d0d] DataValues v0.4.13
  [8bb1440f] DelimitedFiles v1.9.1
  [85a47980] Dictionaries v0.4.6
⌅ [0703355e] DimensionalData v0.29.27
  [6e83dbb3] Discretizers v3.2.4
  [b4f34e82] Distances v0.10.12
  [31c24e10] Distributions v0.25.127
  [ffbed154] DocStringExtensions v0.9.5
  [792122b4] EarlyStopping v0.3.0
  [460bff9d] ExceptionUnwrapping v0.1.11
  [e2ba6199] ExprTools v0.1.10
  [411431e0] Extents v0.1.6
  [4f61f5a4] FFTViews v0.3.2
  [7a1cc6ca] FFTW v1.10.0
  [33837fe5] FeatureSelection v0.2.6
  [5789e2e9] FileIO v1.19.0
  [48062228] FilePathsBase v0.9.24
  [1a297f60] FillArrays v1.16.0
⌅ [53c48c17] FixedPointNumbers v0.8.6
  [069b7b12] FunctionWrappers v1.1.3
  [46192b85] GPUArraysCore v0.2.0
⌅ [92fee26a] GZip v0.6.2
  [c27321d9] Glob v1.5.0
  [a2bd30eb] Graphics v1.1.3
⌃ [86223c79] Graphs v1.13.1
  [f67ccb44] HDF5 v0.17.3
⌅ [cd3eb016] HTTP v1.11.0
  [076d061b] HashArrayMappedTries v0.2.0
  [2c695a8d] HistogramThresholding v0.3.1
  [3e5b6fbb] HostCPUFeatures v0.1.18
  [34004b35] HypergeometricFunctions v0.3.28
  [47d2ed2b] Hyperscript v0.0.5
  [ac1192a8] HypertextLiteral v1.0.0
  [b5f81e59] IOCapture v1.0.0
  [615f187c] IfElse v0.1.1
  [2803e5a7] ImageAxes v0.6.12
  [c817782e] ImageBase v0.1.7
  [cbc4b850] ImageBinarization v0.3.1
  [f332f351] ImageContrastAdjustment v0.3.13
  [a09fc81d] ImageCore v0.10.5
  [89d5987c] ImageCorners v0.1.3
  [51556ac3] ImageDistances v0.2.17
  [6a3955dd] ImageFiltering v0.7.12
  [82e4d734] ImageIO v0.6.9
  [6218d12a] ImageMagick v1.4.2
  [bc367c6b] ImageMetadata v0.9.10
⌃ [787d08f9] ImageMorphology v0.4.6
  [2996bd0c] ImageQualityIndexes v0.3.7
⌃ [80713f31] ImageSegmentation v1.9.0
  [4e3cecfd] ImageShow v0.3.8
  [02fcd773] ImageTransformations v0.10.3
  [916415d5] Images v0.26.2
  [313cdc1a] Indexing v1.1.1
  [9b13fd28] IndirectArrays v1.0.0
  [d25df0c9] Inflate v0.1.5
  [842dd82b] InlineStrings v1.4.5
  [1d092043] IntegralArrays v0.1.6
  [85a1e053] Interfaces v0.3.2
  [7d512f48] InternedStrings v0.7.0
  [a98d9a8b] Interpolations v0.16.3
  [8197267c] IntervalSets v0.7.14
  [41ab1584] InvertedIndices v1.3.1
  [92d709cd] IrrationalConstants v0.2.6
  [c8e1da08] IterTools v1.10.0
  [1c8ee90f] IterableTables v1.0.0
  [b3c1a2ee] IterationControl v0.5.4
  [82899510] IteratorInterfaceExtensions v1.0.0
  [033835bb] JLD2 v0.6.4
  [692b3bcd] JLLWrappers v1.8.0
  [682c06a0] JSON v1.6.1
  [0f8b85d8] JSON3 v1.14.3
  [b835a17e] JpegTurbo v0.1.6
⌅ [aa1ae85d] JuliaInterpreter v0.10.12
  [63c18a36] KernelAbstractions v0.9.41
  [b964fa9f] LaTeXStrings v1.4.0
  [a5e1c1ea] LatinHypercubeSampling v1.9.0
  [10f19ff3] LayoutPointers v0.1.17
  [50d2b5c4] Lazy v0.15.1
  [8cdb02fc] LazyModules v0.3.1
  [92ad9a40] LearnAPI v2.0.1
  [2ab3a3ac] LogExpFunctions v1.0.1
  [e6f89c97] LoggingExtras v1.2.0
  [bdcacae8] LoopVectorization v0.12.174
⌃ [6f1432cf] LoweredCodeUtils v3.6.2
⌅ [23992714] MAT v0.11.5
  [6c6e2e6c] MIMEs v1.1.0
  [c2834f40] MLCore v1.0.2
  [eb30cadb] MLDatasets v0.7.21
  [add582a8] MLJ v0.23.2
  [45f359ea] MLJBalancing v0.1.6
  [a7f614a8] MLJBase v1.13.1
  [50ed68f4] MLJEnsembles v0.4.5
  [614be32b] MLJIteration v0.6.5
  [e80e1ace] MLJModelInterface v1.12.1
  [d491faf4] MLJModels v0.18.8
  [23777cdb] MLJTransforms v0.1.6
  [03970b2e] MLJTuning v0.8.9
  [b5d0f7f3] MLJWrappers v0.1.3
  [f1d291b0] MLUtils v0.4.9
  [3da0fdf6] MPIPreferences v0.1.12
  [1914dd2f] MacroTools v0.5.16
  [d125e4d3] ManualMemory v0.1.8
  [dbb5928d] MappedArrays v0.4.3
  [739be429] MbedTLS v1.1.10
  [eff96d63] Measurements v2.14.1
  [6fafb56a] Memoization v0.2.2
⌅ [626554b9] MetaGraphs v0.8.1
  [e1d29d7a] Missings v1.2.0
  [78c3b35d] Mocking v0.8.1
  [e54bda2e] ModalDecisionTrees v0.5.3
  [e94cdb99] MosaicViews v0.3.4
  [8cc5100c] MultiData v0.1.4
  [872c559c] NNlib v0.9.36
  [15e1cf62] NPZ v0.4.3
  [77ba4419] NaNMath v1.1.4
  [b8a86587] NearestNeighbors v0.4.27
  [f09324ee] Netpbm v1.1.1
  [6fe1bfb0] OffsetArrays v1.17.0
  [52e1d378] OpenEXR v0.3.3
  [8b6db2d4] OpenML v0.3.3
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        Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading.
     Testing Running tests...
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.
Julia version: 1.14.0-DEV.2435

##################################################
TEST: base.jl
┌ Warning: Parity encountered in bestguess! counts (2 elements): Dict("Class_1" => 1, "Class_2" => 1), argmax: Class_1, max: 1 (sum = 2)
└ @ SoleBase ~/.julia/packages/SoleBase/KRa1C/src/machine-learning-utils.jl:96
┌ Warning: Parity encountered in bestguess! counts (2 elements): Dict("Class_1" => 1, "Class_2" => 1), argmax: Class_1, max: 1 (sum = 2)
└ @ SoleBase ~/.julia/packages/SoleBase/KRa1C/src/machine-learning-utils.jl:96
==================================================

##################################################
TEST: classification/japanesevowels.jl
[ Info: Downloading dataset 375.
┌ Warning: Conversion to OrderedDict is deprecated for unordered associative containers (in this case, Dict{Any, Any}). Use an ordered or sorted associative type, such as SortedDict and OrderedDict.
│   caller = Tables.DictColumnTable(schema::Tables.Schema, values::Dict{Any, Any}) at dicts.jl:3 [inlined]
└ @ Tables ~/.julia/packages/Tables/cRTb7/src/dicts.jl:3
┌ Warning: Conversion to OrderedDict is deprecated for unordered associative containers (in this case, Dict{Symbol, AbstractVector}). Use an ordered or sorted associative type, such as SortedDict and OrderedDict.
│   caller = Tables.DictColumnTable(schema::Tables.Schema, values::Dict{Symbol, AbstractVector}) at dicts.jl:3 [inlined]
└ @ Tables ~/.julia/packages/Tables/cRTb7/src/dicts.jl:3
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
164.660394 seconds (99.38 M allocations: 5.650 GiB, 1.37% gc time, 98.38% compilation time: <1% of which was recompilation)
▣ {1}(⟨G⟩(min[B] ≥ -0.32))
├✔ {1}(⟨G⟩((min[B] ≥ -0.32) ∧ ⟨G⟩(min[C] < 0.07)))
│ ├✔ {1}(⟨G⟩((min[B] ≥ -0.32) ∧ ⟨G⟩((min[C] < 0.07) ∧ (max[I] < -0.17))))
│ │ ├✔ 3
│ │ └✘ 4
│ └✘ 1
└✘ {1}(⟨G⟩(min[E] ≥ 0.11))
  ├✔ {1}(⟨G⟩((min[E] ≥ 0.11) ∧ (min[C] < 0.03)))
  │ ├✔ 3
  │ └✘ 2
  └✘ 4
▣ {1}(⟨G⟩(min[b] ≥ -0.318667))
├✔variable_names_map = ["a", "b"]
 {1}(⟨G⟩((min[b] ≥ -0.318667) ∧ ⟨G⟩(min[?V3?] < 0.072986)))
│ ├✔variable_names_map = ["a", "b"]
variable_names_map = ["a", "b"]
 {1}(⟨G⟩((min[b] ≥ -0.318667) ∧ ⟨G⟩((min[?V3?] < 0.072986) ∧ (max[?V9?] < -0.167833))))
│ │ ├✔ 3
│ │ └✘ 4
│ └✘ 1
└✘variable_names_map = ["a", "b"]
 {1}(⟨G⟩(min[?V5?] ≥ 0.114694))
  ├✔variable_names_map = ["a", "b"]
variable_names_map = ["a", "b"]
 {1}(⟨G⟩((min[?V5?] ≥ 0.114694) ∧ (min[?V3?] < 0.031142)))
  │ ├✔ 3
  │ └✘ 2
  └✘ 4
Classification, modal: Log Test Failed at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/classification/japanesevowels.jl:48
  Expression: (report(mach)).printmodel(syntaxstring_kwargs = (; variable_names_map = [["a", "b"]]))
  Log Pattern: (:warn, r"Could not find variable.*") (:warn, r"Could not find variable.*")
  Captured Logs: 
    LogRecord(Warn, "Could not find variable 3 in `variable_names_map`. ([\"a\", \"b\"])", SoleData, Symbol("var-features"), :SoleData_afb02881, "/home/pkgeval/.julia/packages/SoleData/C2yBj/src/scalar/var-features.jl", 173, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}())
    LogRecord(Warn, "Could not find variable 3 in `variable_names_map`. ([\"a\", \"b\"])", SoleData, Symbol("var-features"), :SoleData_afb02881, "/home/pkgeval/.julia/packages/SoleData/C2yBj/src/scalar/var-features.jl", 173, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}())
    LogRecord(Warn, "Could not find variable 9 in `variable_names_map`. ([\"a\", \"b\"])", SoleData, Symbol("var-features"), :SoleData_afb02881, "/home/pkgeval/.julia/packages/SoleData/C2yBj/src/scalar/var-features.jl", 173, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}())
    LogRecord(Warn, "Could not find variable 5 in `variable_names_map`. ([\"a\", \"b\"])", SoleData, Symbol("var-features"), :SoleData_afb02881, "/home/pkgeval/.julia/packages/SoleData/C2yBj/src/scalar/var-features.jl", 173, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}())
    LogRecord(Warn, "Could not find variable 5 in `variable_names_map`. ([\"a\", \"b\"])", SoleData, Symbol("var-features"), :SoleData_afb02881, "/home/pkgeval/.julia/packages/SoleData/C2yBj/src/scalar/var-features.jl", 173, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}())
    LogRecord(Warn, "Could not find variable 3 in `variable_names_map`. ([\"a\", \"b\"])", SoleData, Symbol("var-features"), :SoleData_afb02881, "/home/pkgeval/.julia/packages/SoleData/C2yBj/src/scalar/var-features.jl", 173, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}())

Stacktrace:
  [1] record(ts::Test.DefaultTestSet, t::Test.LogTestFailure)
    @ Test /opt/julia/share/julia/stdlib/v1.14/Test/src/logging.jl:166
  [2] top-level scope
    @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/classification/japanesevowels.jl:48
  [3] include(mapexpr::Function, mod::Module, _path::String)
    @ Base Base.jl:326
  [4] run_tests(list::Vector{String})
    @ Main ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:14
  [5] macro expansion
    @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
  [6] macro expansion
    @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
  [7] macro expansion
    @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
  [8] macro expansion
    @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
  [9] top-level scope
    @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:50
 [10] include(mapexpr::Function, mod::Module, _path::String)
    @ Base Base.jl:326
 [11] top-level scope
    @ none:6
 [12] eval(m::Module, e::Any)
    @ Core boot.jl:522
 [13] exec_options(opts::Base.JLOptions)
    @ Base client.jl:321
 [14] _start()
    @ Base client.jl:596
▣ {1}(⟨G⟩(min[b] ≥ -0.318667))
├✔variable_names_map = ["a", "b"]
 {1}(⟨G⟩((min[b] ≥ -0.318667) ∧ ⟨G⟩(min[?V3?] < 0.072986)))
│ ├✔variable_names_map = ["a", "b"]
variable_names_map = ["a", "b"]
 {1}(⟨G⟩((min[b] ≥ -0.318667) ∧ ⟨G⟩((min[?V3?] < 0.072986) ∧ (max[?V9?] < -0.167833))))
│ │ ├✔ 3
│ │ └✘ 4
│ └✘ 1
└✘variable_names_map = ["a", "b"]
 {1}(⟨G⟩(min[?V5?] ≥ 0.114694))
  ├✔variable_names_map = ["a", "b"]
variable_names_map = ["a", "b"]
 {1}(⟨G⟩((min[?V5?] ≥ 0.114694) ∧ (min[?V3?] < 0.031142)))
  │ ├✔ 3
  │ └✘ 2
  └✘ 4
Classification, modal: Log Test Failed at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/classification/japanesevowels.jl:49
  Expression: (report(mach)).printmodel(syntaxstring_kwargs = (; variable_names_map = ["a", "b"]))
  Log Pattern: (:warn, r"Could not find variable.*") (:warn, r"Could not find variable.*")
  Captured Logs: 
    LogRecord(Warn, "Could not find variable 3 in `variable_names_map`. ([\"a\", \"b\"])", SoleData, Symbol("var-features"), :SoleData_afb02881, "/home/pkgeval/.julia/packages/SoleData/C2yBj/src/scalar/var-features.jl", 173, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}())
    LogRecord(Warn, "Could not find variable 3 in `variable_names_map`. ([\"a\", \"b\"])", SoleData, Symbol("var-features"), :SoleData_afb02881, "/home/pkgeval/.julia/packages/SoleData/C2yBj/src/scalar/var-features.jl", 173, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}())
    LogRecord(Warn, "Could not find variable 9 in `variable_names_map`. ([\"a\", \"b\"])", SoleData, Symbol("var-features"), :SoleData_afb02881, "/home/pkgeval/.julia/packages/SoleData/C2yBj/src/scalar/var-features.jl", 173, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}())
    LogRecord(Warn, "Could not find variable 5 in `variable_names_map`. ([\"a\", \"b\"])", SoleData, Symbol("var-features"), :SoleData_afb02881, "/home/pkgeval/.julia/packages/SoleData/C2yBj/src/scalar/var-features.jl", 173, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}())
    LogRecord(Warn, "Could not find variable 5 in `variable_names_map`. ([\"a\", \"b\"])", SoleData, Symbol("var-features"), :SoleData_afb02881, "/home/pkgeval/.julia/packages/SoleData/C2yBj/src/scalar/var-features.jl", 173, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}())
    LogRecord(Warn, "Could not find variable 3 in `variable_names_map`. ([\"a\", \"b\"])", SoleData, Symbol("var-features"), :SoleData_afb02881, "/home/pkgeval/.julia/packages/SoleData/C2yBj/src/scalar/var-features.jl", 173, Base.Pairs{Symbol, Union{}, Nothing, @NamedTuple{}}())

Stacktrace:
  [1] record(ts::Test.DefaultTestSet, t::Test.LogTestFailure)
    @ Test /opt/julia/share/julia/stdlib/v1.14/Test/src/logging.jl:166
  [2] top-level scope
    @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/classification/japanesevowels.jl:49
  [3] include(mapexpr::Function, mod::Module, _path::String)
    @ Base Base.jl:326
  [4] run_tests(list::Vector{String})
    @ Main ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:14
  [5] macro expansion
    @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
  [6] macro expansion
    @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
  [7] macro expansion
    @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
  [8] macro expansion
    @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
  [9] top-level scope
    @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:50
 [10] include(mapexpr::Function, mod::Module, _path::String)
    @ Base Base.jl:326
 [11] top-level scope
    @ none:6
 [12] eval(m::Module, e::Any)
    @ Core boot.jl:522
 [13] exec_options(opts::Base.JLOptions)
    @ Base client.jl:321
 [14] _start()
    @ Base client.jl:596
▣ {1}(⟨G⟩(min[B] ≥ -0.318667))
├✔ {1}(⟨G⟩((min[B] ≥ -0.318667) ∧ ⟨G⟩(min[C] < 0.072986)))
│ ├✔ {1}(⟨G⟩((min[B] ≥ -0.318667) ∧ ⟨G⟩((min[C] < 0.072986) ∧ (max[I] < -0.167833))))
│ │ ├✔ 3
│ │ └✘ 4
│ └✘ 1
└✘ {1}(⟨G⟩(min[E] ≥ 0.114694))
  ├✔ {1}(⟨G⟩((min[E] ≥ 0.114694) ∧ (min[C] < 0.031142)))
  │ ├✔ 3
  │ └✘ 2
  └✘ 4
▣ {1}(⟨G⟩(min[B] ≥ -0.318667))
├✔ {1}(⟨G⟩((min[B] ≥ -0.318667) ∧ ⟨G⟩(min[C] < 0.072986)))
│ ├✔ {1}(⟨G⟩((min[B] ≥ -0.318667) ∧ ⟨G⟩((min[C] < 0.072986) ∧ (max[I] < -0.167833))))
│ │ ├✔ 3
│ │ └✘ 4
│ └✘ 1
└✘ {1}(⟨G⟩(min[E] ≥ 0.114694))
  ├✔ {1}(⟨G⟩((min[E] ≥ 0.114694) ∧ (min[C] < 0.031142)))
  │ ├✔ 3
  │ └✘ 2
  └✘ 4
▣ {1}(⟨G⟩(min[V2] ≥ -0.318667))
├✔ {1}(⟨G⟩((min[V2] ≥ -0.318667) ∧ ⟨G⟩(min[V3] < 0.072986)))
│ ├✔ {1}(⟨G⟩((min[V2] ≥ -0.318667) ∧ ⟨G⟩((min[V3] < 0.072986) ∧ (max[V9] < -0.167833))))
│ │ ├✔ 3
│ │ └✘ 4
│ └✘ 1
└✘ {1}(⟨G⟩(min[V5] ≥ 0.114694))
  ├✔ {1}(⟨G⟩((min[V5] ≥ 0.114694) ∧ (min[V3] < 0.031142)))
  │ ├✔ 3
  │ └✘ 2
  └✘ 4
▣ (⟨G⟩(min[2] ≥ -0.318667))
├✔ (⟨G⟩((min[2] ≥ -0.318667) ∧ ⟨G⟩(min[3] < 0.072986)))
│ ├✔ (⟨G⟩((min[2] ≥ -0.318667) ∧ ⟨G⟩((min[3] < 0.072986) ∧ (max[9] < -0.167833))))
│ │ ├✔ 3
│ │ └✘ 4
│ └✘ 1
└✘ (⟨G⟩(min[5] ≥ 0.114694))
  ├✔ (⟨G⟩((min[5] ≥ 0.114694) ∧ (min[3] < 0.031142)))
  │ ├✔ 3
  │ └✘ 2
  └✘ 4
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
 35.316777 seconds (36.10 M allocations: 1.459 GiB, 1.11% gc time, 90.97% compilation time: <1% of which was recompilation)
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
  4.278311 seconds (29.31 M allocations: 983.804 MiB, 6.87% gc time, 12.00% compilation time: <1% of which was recompilation)
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
 12.015129 seconds (22.44 M allocations: 786.953 MiB, 6.08% gc time, 74.29% compilation time: <1% of which was recompilation)
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
  2.388187 seconds (7.47 M allocations: 234.800 MiB, 2.88% gc time, 67.12% compilation time: <1% of which was recompilation)
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
  9.542306 seconds (19.01 M allocations: 710.403 MiB, 1.72% gc time, 79.75% compilation time: <1% of which was recompilation)
┌ Warning: An absolute n_subfeatures was provided 2. It is recommended to use relative values (between 0 and 1), interpreted as the share of the random portion of feature space explored at each split.
└ @ ModalDecisionTrees.MLJInterface ~/.julia/packages/ModalDecisionTrees/d9j23/src/interfaces/MLJ/ModalDecisionTree.jl:120
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
 15.161872 seconds (16.05 M allocations: 650.083 MiB, 1.49% gc time, 91.23% compilation time: <1% of which was recompilation)
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
  4.603009 seconds (20.10 M allocations: 690.481 MiB, 4.64% gc time, 49.11% compilation time: <1% of which was recompilation)
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
  4.438473 seconds (29.46 M allocations: 995.245 MiB, 16.72% gc time, 9.96% compilation time: <1% of which was recompilation)
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
┌ Error: Problem fitting the machine machine(ModalDecisionTree(max_depth = nothing, …), …). 
└ @ MLJBase ~/.julia/packages/MLJBase/DCbte/src/machines.jl:695
[ Info: Running type checks... 
[ Info: Type checks okay. 
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
┌ Error: Problem fitting the machine machine(ModalDecisionTree(max_depth = nothing, …), …). 
└ @ MLJBase ~/.julia/packages/MLJBase/DCbte/src/machines.jl:695
[ Info: Running type checks... 
[ Info: Type checks okay. 
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
┌ Error: Problem fitting the machine machine(ModalDecisionTree(max_depth = nothing, …), …). 
└ @ MLJBase ~/.julia/packages/MLJBase/DCbte/src/machines.jl:695
[ Info: Running type checks... 
[ Info: Type checks okay. 
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
┌ Error: Problem fitting the machine machine(ModalDecisionTree(max_depth = nothing, …), …). 
└ @ MLJBase ~/.julia/packages/MLJBase/DCbte/src/machines.jl:695
[ Info: Running type checks... 
[ Info: Type checks okay. 
┌ Warning: AbstractArray of 3 dimensions and size (7, 12, 640) encountered. This will be interpreted as a dataset of 640 instances, 12 variables, and channel size (7,).
└ @ SoleData ~/.julia/packages/SoleData/C2yBj/src/utils/autologiset-tools.jl:237
[ Info: Precomputing logiset...

Computing logiset...   0%|▏                              |  ETA: 0:06:10
Computing logiset... 100%|███████████████████████████████| Time: 0:00:02
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
 33.363852 seconds (186.01 M allocations: 6.804 GiB, 3.52% gc time, 30.59% compilation time: <1% of which was recompilation)
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
 19.156179 seconds (139.71 M allocations: 4.982 GiB, 4.50% gc time, 3.94% compilation time: <1% of which was recompilation)
[ Info: Precomputing logiset...
[ Info: Training machine(ModalAdaBoost(max_depth = 1, …), …).

Applying trees...   8%|██▊                               |  ETA: 0:00:42
Applying trees... 100%|██████████████████████████████████| Time: 0:00:03
▣ Ensemble{String} of 25 models of type DecisionTree{String}
├[1/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.32))
│      ├✔ 1 : (ninstances = 48, ncovered = 48, confidence = 0.5, lift = 1.0)
│      └✘ 2 : (ninstances = 32, ncovered = 32, confidence = 0.81, lift = 1.0)
├[2/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.06))
│      ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│      └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[3/25]┐ {1}(⟨G⟩(minimum⁺[I] ≥ 0.06))
│      ├✔ 4 : (ninstances = 16, ncovered = 16, confidence = 0.44, lift = 1.0)
│      └✘ 2 : (ninstances = 64, ncovered = 64, confidence = 0.39, lift = 1.0)
├[4/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.06))
│      ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│      └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[5/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.41))
│      ├✔ 4 : (ninstances = 50, ncovered = 50, confidence = 0.1, lift = 1.0)
│      └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[6/25]┐ {1}(⟨G⟩(minimum⁻[I] < -0.17))
│      ├✔ 3 : (ninstances = 57, ncovered = 57, confidence = 0.4, lift = 1.0)
│      └✘ 4 : (ninstances = 23, ncovered = 23, confidence = 0.26, lift = 1.0)
├[7/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.41))
│      ├✔ 1 : (ninstances = 50, ncovered = 50, confidence = 0.48, lift = 1.0)
│      └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[8/25]┐ {1}(⟨G⟩(minimum⁺[I] ≥ 0.06))
│      ├✔ 4 : (ninstances = 16, ncovered = 16, confidence = 0.44, lift = 1.0)
│      └✘ 3 : (ninstances = 64, ncovered = 64, confidence = 0.31, lift = 1.0)
├[9/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.32))
│      ├✔ 1 : (ninstances = 48, ncovered = 48, confidence = 0.5, lift = 1.0)
│      └✘ 2 : (ninstances = 32, ncovered = 32, confidence = 0.81, lift = 1.0)
├[10/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.19))
│       ├✔ 3 : (ninstances = 41, ncovered = 41, confidence = 0.44, lift = 1.0)
│       └✘ 4 : (ninstances = 39, ncovered = 39, confidence = 0.15, lift = 1.0)
├[11/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.41))
│       ├✔ 1 : (ninstances = 50, ncovered = 50, confidence = 0.48, lift = 1.0)
│       └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[12/25]┐ {1}(⟨G⟩(minimum⁻[F] < -0.58))
│       ├✔ 3 : (ninstances = 20, ncovered = 20, confidence = 0.9, lift = 1.0)
│       └✘ 4 : (ninstances = 60, ncovered = 60, confidence = 0.1, lift = 1.0)
├[13/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.41))
│       ├✔ 3 : (ninstances = 50, ncovered = 50, confidence = 0.42, lift = 1.0)
│       └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[14/25]┐ {1}(⟨G⟩(minimum⁻[A] < 1.02))
│       ├✔ 4 : (ninstances = 57, ncovered = 57, confidence = 0.12, lift = 1.0)
│       └✘ 1 : (ninstances = 23, ncovered = 23, confidence = 0.96, lift = 1.0)
├[15/25]┐ {1}(⟨G⟩(minimum⁺[C] ≥ 0.21))
│       ├✔ 2 : (ninstances = 57, ncovered = 57, confidence = 0.46, lift = 1.0)
│       └✘ 3 : (ninstances = 23, ncovered = 23, confidence = 0.91, lift = 1.0)
├[16/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.06))
│       ├✔ 3 : (ninstances = 30, ncovered = 30, confidence = 0.77, lift = 1.0)
│       └✘ 1 : (ninstances = 50, ncovered = 50, confidence = 0.48, lift = 1.0)
├[17/25]┐ {1}(⟨G⟩(minimum⁺[D] ≥ -0.45))
│       ├✔ 1 : (ninstances = 44, ncovered = 44, confidence = 0.52, lift = 1.0)
│       └✘ 4 : (ninstances = 36, ncovered = 36, confidence = 0.19, lift = 1.0)
├[18/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.41))
│       ├✔ 4 : (ninstances = 50, ncovered = 50, confidence = 0.1, lift = 1.0)
│       └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[19/25]┐ {1}(⟨G⟩(minimum⁺[A] ≥ 0.95))
│       ├✔ 1 : (ninstances = 32, ncovered = 32, confidence = 0.75, lift = 1.0)
│       └✘ 3 : (ninstances = 48, ncovered = 48, confidence = 0.46, lift = 1.0)
├[20/25]┐ {1}(⟨G⟩(minimum⁺[I] ≥ 0.15))
│       ├✔ 4 : (ninstances = 7, ncovered = 7, confidence = 0.71, lift = 1.0)
│       └✘ 2 : (ninstances = 73, ncovered = 73, confidence = 0.36, lift = 1.0)
├[21/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.06))
│       ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│       └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[22/25]┐ {1}(⟨G⟩(minimum⁻[I] < -0.24))
│       ├✔ 2 : (ninstances = 47, ncovered = 47, confidence = 0.51, lift = 1.0)
│       └✘ 4 : (ninstances = 33, ncovered = 33, confidence = 0.21, lift = 1.0)
├[23/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.06))
│       ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│       └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[24/25]┐ {1}(⟨G⟩(minimum⁻[L] < 0.15))
│       ├✔ 4 : (ninstances = 60, ncovered = 60, confidence = 0.1, lift = 1.0)
│       └✘ 2 : (ninstances = 20, ncovered = 20, confidence = 0.75, lift = 1.0)
└[25/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.06))
        ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
        └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
▣ Ensemble{String} of 25 models of type DecisionTree{String}
├[1/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.318667))
│      ├✔ 1 : (ninstances = 48, ncovered = 48, confidence = 0.5, lift = 1.0)
│      └✘ 2 : (ninstances = 32, ncovered = 32, confidence = 0.81, lift = 1.0)
├[2/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.06279))
│      ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│      └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[3/25]┐ {1}(⟨G⟩(minimum⁺[I] ≥ 0.056958))
│      ├✔ 4 : (ninstances = 16, ncovered = 16, confidence = 0.44, lift = 1.0)
│      └✘ 2 : (ninstances = 64, ncovered = 64, confidence = 0.39, lift = 1.0)
├[4/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.06279))
│      ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│      └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[5/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.408784))
│      ├✔ 4 : (ninstances = 50, ncovered = 50, confidence = 0.1, lift = 1.0)
│      └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[6/25]┐ {1}(⟨G⟩(minimum⁻[I] < -0.165629))
│      ├✔ 3 : (ninstances = 57, ncovered = 57, confidence = 0.4, lift = 1.0)
│      └✘ 4 : (ninstances = 23, ncovered = 23, confidence = 0.26, lift = 1.0)
├[7/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.408784))
│      ├✔ 1 : (ninstances = 50, ncovered = 50, confidence = 0.48, lift = 1.0)
│      └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[8/25]┐ {1}(⟨G⟩(minimum⁺[I] ≥ 0.056958))
│      ├✔ 4 : (ninstances = 16, ncovered = 16, confidence = 0.44, lift = 1.0)
│      └✘ 3 : (ninstances = 64, ncovered = 64, confidence = 0.31, lift = 1.0)
├[9/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.318667))
│      ├✔ 1 : (ninstances = 48, ncovered = 48, confidence = 0.5, lift = 1.0)
│      └✘ 2 : (ninstances = 32, ncovered = 32, confidence = 0.81, lift = 1.0)
├[10/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.193249))
│       ├✔ 3 : (ninstances = 41, ncovered = 41, confidence = 0.44, lift = 1.0)
│       └✘ 4 : (ninstances = 39, ncovered = 39, confidence = 0.15, lift = 1.0)
├[11/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.408784))
│       ├✔ 1 : (ninstances = 50, ncovered = 50, confidence = 0.48, lift = 1.0)
│       └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[12/25]┐ {1}(⟨G⟩(minimum⁻[F] < -0.575495))
│       ├✔ 3 : (ninstances = 20, ncovered = 20, confidence = 0.9, lift = 1.0)
│       └✘ 4 : (ninstances = 60, ncovered = 60, confidence = 0.1, lift = 1.0)
├[13/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.408784))
│       ├✔ 3 : (ninstances = 50, ncovered = 50, confidence = 0.42, lift = 1.0)
│       └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[14/25]┐ {1}(⟨G⟩(minimum⁻[A] < 1.019561))
│       ├✔ 4 : (ninstances = 57, ncovered = 57, confidence = 0.12, lift = 1.0)
│       └✘ 1 : (ninstances = 23, ncovered = 23, confidence = 0.96, lift = 1.0)
├[15/25]┐ {1}(⟨G⟩(minimum⁺[C] ≥ 0.212466))
│       ├✔ 2 : (ninstances = 57, ncovered = 57, confidence = 0.46, lift = 1.0)
│       └✘ 3 : (ninstances = 23, ncovered = 23, confidence = 0.91, lift = 1.0)
├[16/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.064301))
│       ├✔ 3 : (ninstances = 30, ncovered = 30, confidence = 0.77, lift = 1.0)
│       └✘ 1 : (ninstances = 50, ncovered = 50, confidence = 0.48, lift = 1.0)
├[17/25]┐ {1}(⟨G⟩(minimum⁺[D] ≥ -0.446165))
│       ├✔ 1 : (ninstances = 44, ncovered = 44, confidence = 0.52, lift = 1.0)
│       └✘ 4 : (ninstances = 36, ncovered = 36, confidence = 0.19, lift = 1.0)
├[18/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.408784))
│       ├✔ 4 : (ninstances = 50, ncovered = 50, confidence = 0.1, lift = 1.0)
│       └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[19/25]┐ {1}(⟨G⟩(minimum⁺[A] ≥ 0.9481))
│       ├✔ 1 : (ninstances = 32, ncovered = 32, confidence = 0.75, lift = 1.0)
│       └✘ 3 : (ninstances = 48, ncovered = 48, confidence = 0.46, lift = 1.0)
├[20/25]┐ {1}(⟨G⟩(minimum⁺[I] ≥ 0.149199))
│       ├✔ 4 : (ninstances = 7, ncovered = 7, confidence = 0.71, lift = 1.0)
│       └✘ 2 : (ninstances = 73, ncovered = 73, confidence = 0.36, lift = 1.0)
├[21/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.06279))
│       ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│       └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[22/25]┐ {1}(⟨G⟩(minimum⁻[I] < -0.2378))
│       ├✔ 2 : (ninstances = 47, ncovered = 47, confidence = 0.51, lift = 1.0)
│       └✘ 4 : (ninstances = 33, ncovered = 33, confidence = 0.21, lift = 1.0)
├[23/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.06279))
│       ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│       └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[24/25]┐ {1}(⟨G⟩(minimum⁻[L] < 0.145693))
│       ├✔ 4 : (ninstances = 60, ncovered = 60, confidence = 0.1, lift = 1.0)
│       └✘ 2 : (ninstances = 20, ncovered = 20, confidence = 0.75, lift = 1.0)
└[25/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.06279))
        ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
        └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
▣ Ensemble{String} of 25 models of type DecisionTree{String}
├[1/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.318667))
│      ├✔ 1 : (ninstances = 48, ncovered = 48, confidence = 0.5, lift = 1.0)
│      └✘ 2 : (ninstances = 32, ncovered = 32, confidence = 0.81, lift = 1.0)
├[2/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.06279))
│      ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│      └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[3/25]┐ {1}(⟨G⟩(minimum⁺[I] ≥ 0.056958))
│      ├✔ 4 : (ninstances = 16, ncovered = 16, confidence = 0.44, lift = 1.0)
│      └✘ 2 : (ninstances = 64, ncovered = 64, confidence = 0.39, lift = 1.0)
├[4/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.06279))
│      ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│      └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[5/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.408784))
│      ├✔ 4 : (ninstances = 50, ncovered = 50, confidence = 0.1, lift = 1.0)
│      └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[6/25]┐ {1}(⟨G⟩(minimum⁻[I] < -0.165629))
│      ├✔ 3 : (ninstances = 57, ncovered = 57, confidence = 0.4, lift = 1.0)
│      └✘ 4 : (ninstances = 23, ncovered = 23, confidence = 0.26, lift = 1.0)
├[7/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.408784))
│      ├✔ 1 : (ninstances = 50, ncovered = 50, confidence = 0.48, lift = 1.0)
│      └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[8/25]┐ {1}(⟨G⟩(minimum⁺[I] ≥ 0.056958))
│      ├✔ 4 : (ninstances = 16, ncovered = 16, confidence = 0.44, lift = 1.0)
│      └✘ 3 : (ninstances = 64, ncovered = 64, confidence = 0.31, lift = 1.0)
├[9/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.318667))
│      ├✔ 1 : (ninstances = 48, ncovered = 48, confidence = 0.5, lift = 1.0)
│      └✘ 2 : (ninstances = 32, ncovered = 32, confidence = 0.81, lift = 1.0)
├[10/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.193249))
│       ├✔ 3 : (ninstances = 41, ncovered = 41, confidence = 0.44, lift = 1.0)
│       └✘ 4 : (ninstances = 39, ncovered = 39, confidence = 0.15, lift = 1.0)
├[11/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.408784))
│       ├✔ 1 : (ninstances = 50, ncovered = 50, confidence = 0.48, lift = 1.0)
│       └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[12/25]┐ {1}(⟨G⟩(minimum⁻[F] < -0.575495))
│       ├✔ 3 : (ninstances = 20, ncovered = 20, confidence = 0.9, lift = 1.0)
│       └✘ 4 : (ninstances = 60, ncovered = 60, confidence = 0.1, lift = 1.0)
├[13/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.408784))
│       ├✔ 3 : (ninstances = 50, ncovered = 50, confidence = 0.42, lift = 1.0)
│       └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[14/25]┐ {1}(⟨G⟩(minimum⁻[A] < 1.019561))
│       ├✔ 4 : (ninstances = 57, ncovered = 57, confidence = 0.12, lift = 1.0)
│       └✘ 1 : (ninstances = 23, ncovered = 23, confidence = 0.96, lift = 1.0)
├[15/25]┐ {1}(⟨G⟩(minimum⁺[C] ≥ 0.212466))
│       ├✔ 2 : (ninstances = 57, ncovered = 57, confidence = 0.46, lift = 1.0)
│       └✘ 3 : (ninstances = 23, ncovered = 23, confidence = 0.91, lift = 1.0)
├[16/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.064301))
│       ├✔ 3 : (ninstances = 30, ncovered = 30, confidence = 0.77, lift = 1.0)
│       └✘ 1 : (ninstances = 50, ncovered = 50, confidence = 0.48, lift = 1.0)
├[17/25]┐ {1}(⟨G⟩(minimum⁺[D] ≥ -0.446165))
│       ├✔ 1 : (ninstances = 44, ncovered = 44, confidence = 0.52, lift = 1.0)
│       └✘ 4 : (ninstances = 36, ncovered = 36, confidence = 0.19, lift = 1.0)
├[18/25]┐ {1}(⟨G⟩(minimum⁺[B] ≥ -0.408784))
│       ├✔ 4 : (ninstances = 50, ncovered = 50, confidence = 0.1, lift = 1.0)
│       └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[19/25]┐ {1}(⟨G⟩(minimum⁺[A] ≥ 0.9481))
│       ├✔ 1 : (ninstances = 32, ncovered = 32, confidence = 0.75, lift = 1.0)
│       └✘ 3 : (ninstances = 48, ncovered = 48, confidence = 0.46, lift = 1.0)
├[20/25]┐ {1}(⟨G⟩(minimum⁺[I] ≥ 0.149199))
│       ├✔ 4 : (ninstances = 7, ncovered = 7, confidence = 0.71, lift = 1.0)
│       └✘ 2 : (ninstances = 73, ncovered = 73, confidence = 0.36, lift = 1.0)
├[21/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.06279))
│       ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│       └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[22/25]┐ {1}(⟨G⟩(minimum⁻[I] < -0.2378))
│       ├✔ 2 : (ninstances = 47, ncovered = 47, confidence = 0.51, lift = 1.0)
│       └✘ 4 : (ninstances = 33, ncovered = 33, confidence = 0.21, lift = 1.0)
├[23/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.06279))
│       ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│       └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[24/25]┐ {1}(⟨G⟩(minimum⁻[L] < 0.145693))
│       ├✔ 4 : (ninstances = 60, ncovered = 60, confidence = 0.1, lift = 1.0)
│       └✘ 2 : (ninstances = 20, ncovered = 20, confidence = 0.75, lift = 1.0)
└[25/25]┐ {1}(⟨G⟩(minimum⁻[C] < 0.06279))
        ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
        └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
▣ Ensemble{String} of 25 models of type DecisionTree{String}
├[1/25]┐ {1}(⟨G⟩(minimum⁺[V2] ≥ -0.318667))
│      ├✔ 1 : (ninstances = 48, ncovered = 48, confidence = 0.5, lift = 1.0)
│      └✘ 2 : (ninstances = 32, ncovered = 32, confidence = 0.81, lift = 1.0)
├[2/25]┐ {1}(⟨G⟩(minimum⁻[V3] < 0.06279))
│      ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│      └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[3/25]┐ {1}(⟨G⟩(minimum⁺[V9] ≥ 0.056958))
│      ├✔ 4 : (ninstances = 16, ncovered = 16, confidence = 0.44, lift = 1.0)
│      └✘ 2 : (ninstances = 64, ncovered = 64, confidence = 0.39, lift = 1.0)
├[4/25]┐ {1}(⟨G⟩(minimum⁻[V3] < 0.06279))
│      ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│      └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[5/25]┐ {1}(⟨G⟩(minimum⁺[V2] ≥ -0.408784))
│      ├✔ 4 : (ninstances = 50, ncovered = 50, confidence = 0.1, lift = 1.0)
│      └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[6/25]┐ {1}(⟨G⟩(minimum⁻[V9] < -0.165629))
│      ├✔ 3 : (ninstances = 57, ncovered = 57, confidence = 0.4, lift = 1.0)
│      └✘ 4 : (ninstances = 23, ncovered = 23, confidence = 0.26, lift = 1.0)
├[7/25]┐ {1}(⟨G⟩(minimum⁺[V2] ≥ -0.408784))
│      ├✔ 1 : (ninstances = 50, ncovered = 50, confidence = 0.48, lift = 1.0)
│      └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[8/25]┐ {1}(⟨G⟩(minimum⁺[V9] ≥ 0.056958))
│      ├✔ 4 : (ninstances = 16, ncovered = 16, confidence = 0.44, lift = 1.0)
│      └✘ 3 : (ninstances = 64, ncovered = 64, confidence = 0.31, lift = 1.0)
├[9/25]┐ {1}(⟨G⟩(minimum⁺[V2] ≥ -0.318667))
│      ├✔ 1 : (ninstances = 48, ncovered = 48, confidence = 0.5, lift = 1.0)
│      └✘ 2 : (ninstances = 32, ncovered = 32, confidence = 0.81, lift = 1.0)
├[10/25]┐ {1}(⟨G⟩(minimum⁺[V2] ≥ -0.193249))
│       ├✔ 3 : (ninstances = 41, ncovered = 41, confidence = 0.44, lift = 1.0)
│       └✘ 4 : (ninstances = 39, ncovered = 39, confidence = 0.15, lift = 1.0)
├[11/25]┐ {1}(⟨G⟩(minimum⁺[V2] ≥ -0.408784))
│       ├✔ 1 : (ninstances = 50, ncovered = 50, confidence = 0.48, lift = 1.0)
│       └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[12/25]┐ {1}(⟨G⟩(minimum⁻[V6] < -0.575495))
│       ├✔ 3 : (ninstances = 20, ncovered = 20, confidence = 0.9, lift = 1.0)
│       └✘ 4 : (ninstances = 60, ncovered = 60, confidence = 0.1, lift = 1.0)
├[13/25]┐ {1}(⟨G⟩(minimum⁺[V2] ≥ -0.408784))
│       ├✔ 3 : (ninstances = 50, ncovered = 50, confidence = 0.42, lift = 1.0)
│       └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[14/25]┐ {1}(⟨G⟩(minimum⁻[V1] < 1.019561))
│       ├✔ 4 : (ninstances = 57, ncovered = 57, confidence = 0.12, lift = 1.0)
│       └✘ 1 : (ninstances = 23, ncovered = 23, confidence = 0.96, lift = 1.0)
├[15/25]┐ {1}(⟨G⟩(minimum⁺[V3] ≥ 0.212466))
│       ├✔ 2 : (ninstances = 57, ncovered = 57, confidence = 0.46, lift = 1.0)
│       └✘ 3 : (ninstances = 23, ncovered = 23, confidence = 0.91, lift = 1.0)
├[16/25]┐ {1}(⟨G⟩(minimum⁻[V3] < 0.064301))
│       ├✔ 3 : (ninstances = 30, ncovered = 30, confidence = 0.77, lift = 1.0)
│       └✘ 1 : (ninstances = 50, ncovered = 50, confidence = 0.48, lift = 1.0)
├[17/25]┐ {1}(⟨G⟩(minimum⁺[V4] ≥ -0.446165))
│       ├✔ 1 : (ninstances = 44, ncovered = 44, confidence = 0.52, lift = 1.0)
│       └✘ 4 : (ninstances = 36, ncovered = 36, confidence = 0.19, lift = 1.0)
├[18/25]┐ {1}(⟨G⟩(minimum⁺[V2] ≥ -0.408784))
│       ├✔ 4 : (ninstances = 50, ncovered = 50, confidence = 0.1, lift = 1.0)
│       └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[19/25]┐ {1}(⟨G⟩(minimum⁺[V1] ≥ 0.9481))
│       ├✔ 1 : (ninstances = 32, ncovered = 32, confidence = 0.75, lift = 1.0)
│       └✘ 3 : (ninstances = 48, ncovered = 48, confidence = 0.46, lift = 1.0)
├[20/25]┐ {1}(⟨G⟩(minimum⁺[V9] ≥ 0.149199))
│       ├✔ 4 : (ninstances = 7, ncovered = 7, confidence = 0.71, lift = 1.0)
│       └✘ 2 : (ninstances = 73, ncovered = 73, confidence = 0.36, lift = 1.0)
├[21/25]┐ {1}(⟨G⟩(minimum⁻[V3] < 0.06279))
│       ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│       └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[22/25]┐ {1}(⟨G⟩(minimum⁻[V9] < -0.2378))
│       ├✔ 2 : (ninstances = 47, ncovered = 47, confidence = 0.51, lift = 1.0)
│       └✘ 4 : (ninstances = 33, ncovered = 33, confidence = 0.21, lift = 1.0)
├[23/25]┐ {1}(⟨G⟩(minimum⁻[V3] < 0.06279))
│       ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│       └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[24/25]┐ {1}(⟨G⟩(minimum⁻[V12] < 0.145693))
│       ├✔ 4 : (ninstances = 60, ncovered = 60, confidence = 0.1, lift = 1.0)
│       └✘ 2 : (ninstances = 20, ncovered = 20, confidence = 0.75, lift = 1.0)
└[25/25]┐ {1}(⟨G⟩(minimum⁻[V3] < 0.06279))
        ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
        └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
▣ Ensemble{String} of 25 models of type DecisionTree{String}
├[1/25]┐ (⟨G⟩(minimum⁺[coefficient2] ≥ -0.318667))
│      ├✔ 1 : (ninstances = 48, ncovered = 48, confidence = 0.5, lift = 1.0)
│      └✘ 2 : (ninstances = 32, ncovered = 32, confidence = 0.81, lift = 1.0)
├[2/25]┐ (⟨G⟩(minimum⁻[coefficient3] < 0.06279))
│      ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│      └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[3/25]┐ (⟨G⟩(minimum⁺[coefficient9] ≥ 0.056958))
│      ├✔ 4 : (ninstances = 16, ncovered = 16, confidence = 0.44, lift = 1.0)
│      └✘ 2 : (ninstances = 64, ncovered = 64, confidence = 0.39, lift = 1.0)
├[4/25]┐ (⟨G⟩(minimum⁻[coefficient3] < 0.06279))
│      ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│      └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[5/25]┐ (⟨G⟩(minimum⁺[coefficient2] ≥ -0.408784))
│      ├✔ 4 : (ninstances = 50, ncovered = 50, confidence = 0.1, lift = 1.0)
│      └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[6/25]┐ (⟨G⟩(minimum⁻[coefficient9] < -0.165629))
│      ├✔ 3 : (ninstances = 57, ncovered = 57, confidence = 0.4, lift = 1.0)
│      └✘ 4 : (ninstances = 23, ncovered = 23, confidence = 0.26, lift = 1.0)
├[7/25]┐ (⟨G⟩(minimum⁺[coefficient2] ≥ -0.408784))
│      ├✔ 1 : (ninstances = 50, ncovered = 50, confidence = 0.48, lift = 1.0)
│      └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[8/25]┐ (⟨G⟩(minimum⁺[coefficient9] ≥ 0.056958))
│      ├✔ 4 : (ninstances = 16, ncovered = 16, confidence = 0.44, lift = 1.0)
│      └✘ 3 : (ninstances = 64, ncovered = 64, confidence = 0.31, lift = 1.0)
├[9/25]┐ (⟨G⟩(minimum⁺[coefficient2] ≥ -0.318667))
│      ├✔ 1 : (ninstances = 48, ncovered = 48, confidence = 0.5, lift = 1.0)
│      └✘ 2 : (ninstances = 32, ncovered = 32, confidence = 0.81, lift = 1.0)
├[10/25]┐ (⟨G⟩(minimum⁺[coefficient2] ≥ -0.193249))
│       ├✔ 3 : (ninstances = 41, ncovered = 41, confidence = 0.44, lift = 1.0)
│       └✘ 4 : (ninstances = 39, ncovered = 39, confidence = 0.15, lift = 1.0)
├[11/25]┐ (⟨G⟩(minimum⁺[coefficient2] ≥ -0.408784))
│       ├✔ 1 : (ninstances = 50, ncovered = 50, confidence = 0.48, lift = 1.0)
│       └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[12/25]┐ (⟨G⟩(minimum⁻[coefficient6] < -0.575495))
│       ├✔ 3 : (ninstances = 20, ncovered = 20, confidence = 0.9, lift = 1.0)
│       └✘ 4 : (ninstances = 60, ncovered = 60, confidence = 0.1, lift = 1.0)
├[13/25]┐ (⟨G⟩(minimum⁺[coefficient2] ≥ -0.408784))
│       ├✔ 3 : (ninstances = 50, ncovered = 50, confidence = 0.42, lift = 1.0)
│       └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[14/25]┐ (⟨G⟩(minimum⁻[coefficient1] < 1.019561))
│       ├✔ 4 : (ninstances = 57, ncovered = 57, confidence = 0.12, lift = 1.0)
│       └✘ 1 : (ninstances = 23, ncovered = 23, confidence = 0.96, lift = 1.0)
├[15/25]┐ (⟨G⟩(minimum⁺[coefficient3] ≥ 0.212466))
│       ├✔ 2 : (ninstances = 57, ncovered = 57, confidence = 0.46, lift = 1.0)
│       └✘ 3 : (ninstances = 23, ncovered = 23, confidence = 0.91, lift = 1.0)
├[16/25]┐ (⟨G⟩(minimum⁻[coefficient3] < 0.064301))
│       ├✔ 3 : (ninstances = 30, ncovered = 30, confidence = 0.77, lift = 1.0)
│       └✘ 1 : (ninstances = 50, ncovered = 50, confidence = 0.48, lift = 1.0)
├[17/25]┐ (⟨G⟩(minimum⁺[coefficient4] ≥ -0.446165))
│       ├✔ 1 : (ninstances = 44, ncovered = 44, confidence = 0.52, lift = 1.0)
│       └✘ 4 : (ninstances = 36, ncovered = 36, confidence = 0.19, lift = 1.0)
├[18/25]┐ (⟨G⟩(minimum⁺[coefficient2] ≥ -0.408784))
│       ├✔ 4 : (ninstances = 50, ncovered = 50, confidence = 0.1, lift = 1.0)
│       └✘ 2 : (ninstances = 30, ncovered = 30, confidence = 0.87, lift = 1.0)
├[19/25]┐ (⟨G⟩(minimum⁺[coefficient1] ≥ 0.9481))
│       ├✔ 1 : (ninstances = 32, ncovered = 32, confidence = 0.75, lift = 1.0)
│       └✘ 3 : (ninstances = 48, ncovered = 48, confidence = 0.46, lift = 1.0)
├[20/25]┐ (⟨G⟩(minimum⁺[coefficient9] ≥ 0.149199))
│       ├✔ 4 : (ninstances = 7, ncovered = 7, confidence = 0.71, lift = 1.0)
│       └✘ 2 : (ninstances = 73, ncovered = 73, confidence = 0.36, lift = 1.0)
├[21/25]┐ (⟨G⟩(minimum⁻[coefficient3] < 0.06279))
│       ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│       └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[22/25]┐ (⟨G⟩(minimum⁻[coefficient9] < -0.2378))
│       ├✔ 2 : (ninstances = 47, ncovered = 47, confidence = 0.51, lift = 1.0)
│       └✘ 4 : (ninstances = 33, ncovered = 33, confidence = 0.21, lift = 1.0)
├[23/25]┐ (⟨G⟩(minimum⁻[coefficient3] < 0.06279))
│       ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
│       └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
├[24/25]┐ (⟨G⟩(minimum⁻[coefficient12] < 0.145693))
│       ├✔ 4 : (ninstances = 60, ncovered = 60, confidence = 0.1, lift = 1.0)
│       └✘ 2 : (ninstances = 20, ncovered = 20, confidence = 0.75, lift = 1.0)
└[25/25]┐ (⟨G⟩(minimum⁻[coefficient3] < 0.06279))
        ├✔ 3 : (ninstances = 29, ncovered = 29, confidence = 0.79, lift = 1.0)
        └✘ 1 : (ninstances = 51, ncovered = 51, confidence = 0.47, lift = 1.0)
[ Info: Not retraining machine(ModalAdaBoost(max_depth = 1, …), …). Use `force=true` to force.
  0.143537 seconds (13.30 k allocations: 744.859 KiB, 99.25% compilation time)
==================================================
TEST: classification/digits.jl
[ Info: Precomputing logiset...

Computing logiset...   0%|                               |  ETA: 0:22:49
Computing logiset... 100%|███████████████████████████████| Time: 0:00:01
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
353.039864 seconds (152.75 M allocations: 9.772 GiB, 1.17% gc time, 98.10% compilation time: <1% of which was recompilation)

Classification, modal: Test Failed at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:40
  Expression: nnodes((fitted_params(mach)).rawmodel) == 55
   Evaluated: 47 == 55
  Stacktrace:
   [1] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:560
   [2] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined]
   [3] include(mapexpr::Function, mod::Module, _path::String)
     @ Base Base.jl:326
   [4] run_tests(list::Vector{String})
     @ Main ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:14
   [5] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [6] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [7] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [8] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [9] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:50
┌ Warning: n_subfeatures must be > 0, but 0 was provided. Defaulting to nothing.
└ @ ModalDecisionTrees.MLJInterface ~/.julia/packages/ModalDecisionTrees/d9j23/src/interfaces/MLJ/ModalDecisionTree.jl:120
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = 6, …), …).
 22.800541 seconds (22.13 M allocations: 1.973 GiB, 5.82% gc time, 75.04% compilation time: <1% of which was recompilation)

Classification, modal: Test Failed at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:49
  Expression: nnodes((fitted_params(mach)).rawmodel) == 47
   Evaluated: 35 == 47
  Stacktrace:
   [1] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:560
   [2] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined]
   [3] include(mapexpr::Function, mod::Module, _path::String)
     @ Base Base.jl:326
   [4] run_tests(list::Vector{String})
     @ Main ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:14
   [5] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [6] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [7] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [8] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [9] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:50
[ Info: Precomputing logiset...
[ Info: Training machine(ModalRandomForest(sampling_fraction = 0.7, …), …).

Classification, modal: Test Failed at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:63
  Expression: nnodes((fitted_params(mach)).rawmodel) == 676
   Evaluated: 702 == 676
  Stacktrace:
   [1] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:560
   [2] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined]
   [3] include(mapexpr::Function, mod::Module, _path::String)
     @ Base Base.jl:326
   [4] run_tests(list::Vector{String})
     @ Main ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:14
   [5] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [6] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [7] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [8] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [9] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:50

Classification, modal: Test Failed at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:66
  Expression: sum(predict_mode(mach, rows = test_idxs) .== y[test_idxs]) / length(y[test_idxs]) > 0.53
   Evaluated: 0.5238095238095238 > 0.53
  Stacktrace:
   [1] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:560
   [2] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined]
   [3] include(mapexpr::Function, mod::Module, _path::String)
     @ Base Base.jl:326
   [4] run_tests(list::Vector{String})
     @ Main ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:14
   [5] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [6] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [7] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [8] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [9] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:50
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
  8.115873 seconds (19.96 M allocations: 1.854 GiB, 6.12% gc time, 0.24% compilation time: <1% of which was recompilation)

Classification, modal: Test Failed at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:73
  Expression: nnodes((fitted_params(mach)).rawmodel) == 55
   Evaluated: 47 == 55
  Stacktrace:
   [1] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:560
   [2] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined]
   [3] include(mapexpr::Function, mod::Module, _path::String)
     @ Base Base.jl:326
   [4] run_tests(list::Vector{String})
     @ Main ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:14
   [5] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [6] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [7] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [8] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [9] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:50
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
139.899798 seconds (55.99 M allocations: 3.884 GiB, 1.79% gc time, 95.78% compilation time: <1% of which was recompilation)
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
 99.184924 seconds (92.47 M allocations: 4.398 GiB, 3.05% gc time, 90.76% compilation time: <1% of which was recompilation)

Classification, modal: Test Failed at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:90
  Expression: nnodes((fitted_params(mach)).rawmodel) == 55
   Evaluated: 47 == 55
  Stacktrace:
   [1] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:560
   [2] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined]
   [3] include(mapexpr::Function, mod::Module, _path::String)
     @ Base Base.jl:326
   [4] run_tests(list::Vector{String})
     @ Main ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:14
   [5] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [6] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [7] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [8] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [9] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:50
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = nothing, …), …).
  4.442576 seconds (19.96 M allocations: 1.854 GiB, 8.69% gc time, 0.41% compilation time: <1% of which was recompilation)

Classification, modal: Test Failed at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:99
  Expression: nnodes((fitted_params(mach)).rawmodel) == 55
   Evaluated: 47 == 55
  Stacktrace:
   [1] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:560
   [2] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined]
   [3] include(mapexpr::Function, mod::Module, _path::String)
     @ Base Base.jl:326
   [4] run_tests(list::Vector{String})
     @ Main ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:14
   [5] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [6] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [7] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [8] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [9] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:50
┌ Warning: n_subfeatures must be > 0, but 0 was provided. Defaulting to nothing.
└ @ ModalDecisionTrees.MLJInterface ~/.julia/packages/ModalDecisionTrees/d9j23/src/interfaces/MLJ/ModalDecisionTree.jl:120
[ Info: Precomputing logiset...
[ Info: Training machine(ModalDecisionTree(max_depth = 6, …), …).
  4.309220 seconds (18.25 M allocations: 1.751 GiB, 37.11% gc time, 0.48% compilation time: <1% of which was recompilation)

Classification, modal: Test Failed at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:107
  Expression: nnodes((fitted_params(mach)).rawmodel) == 47
   Evaluated: 35 == 47
  Stacktrace:
   [1] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:560
   [2] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined]
   [3] include(mapexpr::Function, mod::Module, _path::String)
     @ Base Base.jl:326
   [4] run_tests(list::Vector{String})
     @ Main ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:14
   [5] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [6] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [7] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [8] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [9] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:50
┌ Warning: Assignment to `mach` in soft scope is ambiguous because a global variable by the same name exists: `mach` will be treated as a new local. Disambiguate by using `local mach` to suppress this warning or `global mach` to assign to the existing global variable.
└ @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:111
┌ Warning: An absolute n_subfeatures was provided 3. It is recommended to use relative values (between 0 and 1), interpreted as the share of the random portion of feature space explored at each split.
└ @ ModalDecisionTrees.MLJInterface ~/.julia/packages/ModalDecisionTrees/d9j23/src/interfaces/MLJ/ModalRandomForest.jl:125
[ Info: Precomputing logiset...
[ Info: Training machine(ModalRandomForest(sampling_fraction = 0.7, …), …).
┌ Error: Problem fitting the machine machine(ModalRandomForest(sampling_fraction = 0.7, …), …). 
└ @ MLJBase ~/.julia/packages/MLJBase/DCbte/src/machines.jl:695
[ Info: Running type checks... 
[ Info: Type checks okay. 
[ Info: Precomputing logiset...
[ Info: Training machine(ModalRandomForest(sampling_fraction = 0.7, …), …).

Classification, modal: Test Failed at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:132
  Expression: nnodes((fitted_params(mach)).rawmodel) == 702
   Evaluated: 746 == 702
  Stacktrace:
   [1] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/classification/digits.jl:560
   [2] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:784 [inlined]
   [3] include(mapexpr::Function, mod::Module, _path::String)
     @ Base Base.jl:326
   [4] run_tests(list::Vector{String})
     @ Main ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:14
   [5] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [6] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [7] macro expansion
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55 [inlined]
   [8] macro expansion
     @ /opt/julia/share/julia/stdlib/v1.14/Test/src/Test.jl:2246 [inlined]
   [9] top-level scope
     @ ~/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:50
==================================================
TEST: classification/mnist.jl
[ Info: Precomputing logiset...

======================================================================================
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 106 running 1 of 1

signal (10): User defined signal 1
ijl_types_equal at /source/src/subtype.c:2994:8
ijl_isa at /source/src/subtype.c:3169:24
jl_tuple1_isa at /source/src/subtype.c:3086:18
jl_typemap_entry_assoc_exact at /source/src/typemap.c:1188:25
jl_typemap_assoc_exact at /source/src/julia_internal.h:1963:16 [inlined]
jl_typemap_level_assoc_exact at /source/src/typemap.c:1222:38
jl_typemap_assoc_exact at /source/src/julia_internal.h:1967:16 [inlined]
jl_lookup_generic_ at /source/src/gf.c:4510:21
ijl_apply_generic at /source/src/gf.c:4582:35
isbitstype at ./runtime_internals.jl:892:0 (pc: 4)
isbits at ./runtime_internals.jl:899:0 [inlined]
_deepcopy_memory_t at ./deepcopy.jl:119:0 (pc: 108)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_invoke at /source/src/gf.c:4355:12
deepcopy_internal at ./deepcopy.jl:104:0 [inlined]
deepcopy_internal at ./deepcopy.jl:142:0 (pc: 48)
deepcopy_internal at ./deepcopy.jl:133:0 (pc: 65)
unknown function (ip: 0x70d61f5991b6) at (unknown file)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
deepcopy_internal at ./deepcopy.jl:87:0 (pc: 156)
unknown function (ip: 0x70d61f51bc66) at (unknown file)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
deepcopy_internal at ./deepcopy.jl:87:0 (pc: 156)
#deepcopy_internal##0 at ./deepcopy.jl:40:0 [inlined]
ntuple at ./ntuple.jl:19:0 [inlined]
deepcopy_internal at ./deepcopy.jl:39:0 (pc: 3)
unknown function (ip: 0x70d61f5984fc) at (unknown file)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
deepcopy_internal at ./deepcopy.jl:87:0 (pc: 156)
unknown function (ip: 0x70d61f51bc66) at (unknown file)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
_deepcopy_memory_t at ./deepcopy.jl:120:0 (pc: 111)
deepcopy_internal at ./deepcopy.jl:104:0 [inlined]
deepcopy_internal at ./deepcopy.jl:142:0 (pc: 48)
deepcopy_internal at ./deepcopy.jl:133:0 (pc: 65)
deepcopy_internal at ./deepcopy.jl:87:0 [inlined]
deepcopy at ./deepcopy.jl:34:0 [inlined]
#slicedataset#1 at /home/pkgeval/.julia/packages/SoleBase/KRa1C/src/SoleBase.jl:65:0 [inlined]
slicedataset at /home/pkgeval/.julia/packages/SoleBase/KRa1C/src/SoleBase.jl:57:0 [inlined]
#subset#536 at /home/pkgeval/.julia/packages/SoleData/C2yBj/src/types/logiset-MLJ-interface.jl:56:0 [inlined]
subset at /home/pkgeval/.julia/packages/SoleData/C2yBj/src/types/logiset-MLJ-interface.jl:55:0 [inlined]
selectrows at /home/pkgeval/.julia/packages/SoleData/C2yBj/src/types/logiset-MLJ-interface.jl:95:0 [inlined]
selectrows at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/src/interfaces/MLJ.jl:201:0 (pc: 9)
unknown function (ip: 0x70d61f595b7a) at (unknown file)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
jl_apply at /source/src/julia.h:2405:12 [inlined]
jl_f__apply_iterate at /source/src/builtins.c:918:26
#fit_only!#62 at /home/pkgeval/.julia/packages/MLJBase/DCbte/src/machines.jl:677:0 (pc: 101)
fit_only! at /home/pkgeval/.julia/packages/MLJBase/DCbte/src/machines.jl:617:0 [inlined]
#fit!#70 at /home/pkgeval/.julia/packages/MLJBase/DCbte/src/machines.jl:790:0 [inlined]
fit! at /home/pkgeval/.julia/packages/MLJBase/DCbte/src/machines.jl:787:0 [inlined]
|> at ./operators.jl:983:0 (pc: 4)
unknown function (ip: 0x70d61f518cc2) at (unknown file)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
macro expansion at ./timing.jl:741:0 [inlined]
top-level scope at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/classification/mnist.jl:37:0 (pc: 102)
jl_invoke_oneshot at /source/src/gf.c:4383:23
ijl_eval_thunk at /source/src/toplevel.c:756:18
jl_toplevel_eval_flex at /source/src/toplevel.c:708:26
jl_eval_toplevel_stmts at /source/src/toplevel.c:598:15
jl_toplevel_eval_flex at /source/src/toplevel.c:680:27
ijl_toplevel_eval at /source/src/toplevel.c:778:12
ijl_toplevel_eval_in at /source/src/toplevel.c:823:13
eval at ./boot.jl:522:0 (pc: 1)
include_string at ./loading.jl:3132:0 (pc: 190)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
_include at ./loading.jl:3192:0 (pc: 122)
include at ./Base.jl:326:0 (pc: 1)
IncludeInto at ./Base.jl:327:0 [inlined]
run_tests at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:14:0 (pc: 42)
unknown function (ip: 0x70d653f22e72) at (unknown file)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
macro expansion at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55:0 [inlined]
macro expansion at /source/usr/share/julia/stdlib/v1.14/Test/src/Test.jl:2246:0 [inlined]
macro expansion at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55:0 [inlined]
macro expansion at /source/usr/share/julia/stdlib/v1.14/Test/src/Test.jl:2246:0 [inlined]
top-level scope at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:50:0 (pc: 500)
jl_invoke_oneshot at /source/src/gf.c:4383:23
ijl_eval_thunk at /source/src/toplevel.c:756:18
jl_toplevel_eval_flex at /source/src/toplevel.c:708:26
jl_eval_toplevel_stmts at /source/src/toplevel.c:598:15
jl_toplevel_eval_flex at /source/src/toplevel.c:680:27
ijl_toplevel_eval at /source/src/toplevel.c:778:12
ijl_toplevel_eval_in at /source/src/toplevel.c:823:13
eval at ./boot.jl:522:0 (pc: 1)
include_string at ./loading.jl:3132:0 (pc: 208)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
_include at ./loading.jl:3192:0 (pc: 122)
include at ./Base.jl:326:0 (pc: 1)
IncludeInto at ./Base.jl:327:0 (pc: 2)
jfptr_IncludeInto_1.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
jl_apply at /source/src/julia.h:2405:12 [inlined]
do_call at /source/src/interpreter.c:123:26
eval_value at /source/src/interpreter.c:259:16
eval_stmt_value at /source/src/interpreter.c:194:23 [inlined]
eval_body at /source/src/interpreter.c:757:13
jl_interpret_toplevel_thunk at /source/src/interpreter.c:947:21
ijl_eval_thunk at /source/src/toplevel.c:764:18
jl_toplevel_eval_flex at /source/src/toplevel.c:708:26
jl_eval_toplevel_stmts at /source/src/toplevel.c:598:15
jl_toplevel_eval_flex at /source/src/toplevel.c:680:27
ijl_toplevel_eval at /source/src/toplevel.c:778:12
ijl_toplevel_eval_in at /source/src/toplevel.c:823:13
eval at ./boot.jl:522:0 (pc: 1)
exec_options at ./client.jl:321:0 (pc: 426)
_start at ./client.jl:596:0 (pc: 295)
jfptr__start_0.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
jl_apply at /source/src/julia.h:2405:12 [inlined]
true_main at /source/src/jlapi.c:985:29
jl_repl_entrypoint at /source/src/jlapi.c:1152:15
main at /source/cli/loader_exe.c:58:15
unknown function (ip: 0x70d66eb14249) at /lib/x86_64-linux-gnu/libc.so.6
__libc_start_main at /lib/x86_64-linux-gnu/libc.so.6 (unknown line)
unknown function (ip: 0x4010b8) at /workspace/srcdir/glibc-2.17/csu/../sysdeps/x86_64/start.S
unknown function (ip: (nil)) at (unknown file)


==============================================================
Profile collected. A report will print at the next yield point.
Disabling --trace-compile
==============================================================


======================================================================================
Information request received. A stacktrace will print followed by a 1.0 second profile.
--trace-compile is enabled during profile collection.
======================================================================================

cmd: /opt/julia/bin/julia 1 running 0 of 1

signal (10): User defined signal 1
epoll_pwait at /lib/x86_64-linux-gnu/libc.so.6 (unknown line)
uv__io_poll at /workspace/srcdir/libuv/src/unix/linux.c:1404:0
uv_run at /workspace/srcdir/libuv/src/unix/core.c:430:0
ijl_task_get_next at /source/src/scheduler.c:524:34
wait at ./task.jl:1248:0 (pc: 107)
wait_forever at ./task.jl:1170:0 (pc: 4)
jfptr_wait_forever_0.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
jl_apply at /source/src/julia.h:2405:12 [inlined]
start_task at /source/src/task.c:1276:19
unknown function (ip: (nil)) at (unknown file)


==============================================================
Profile collected. A report will print at the next yield point.
Disabling --trace-compile
==============================================================

┌ Warning: There were no samples collected in one or more groups.
│ This may be due to idle threads, or you may need to run your
│ program longer (perhaps by running it multiple times),
│ or adjust the delay between samples with `Profile.init()`.
└ @ Profile /opt/julia/share/julia/stdlib/v1.14/Profile/src/Profile.jl:1361
Overhead ╎ [+additional indent] Count File:Line  Function
=========================================================
Thread 1 (default) Task 0x0000713d8003e950 Total snapshots: 482. Utilization: 0%
   ╎482 @Base/task.jl:1170  wait_forever()
481╎ 482 @Base/task.jl:1248  wait()


[1] signal 15: Terminated
in expression starting at /PkgEval.jl/scripts/evaluate.jl:214
epoll_pwait at /lib/x86_64-linux-gnu/libc.so.6 (unknown line)
uv__io_poll at /workspace/srcdir/libuv/src/unix/linux.c:1404:0
uv_run at /workspace/srcdir/libuv/src/unix/core.c:430:0
ijl_task_get_next at /source/src/scheduler.c:524:34
wait at ./task.jl:1248:0 (pc: 107)
wait_forever at ./task.jl:1170:0 (pc: 4)
jfptr_wait_forever_0.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
jl_apply at /source/src/julia.h:2405:12 [inlined]
start_task at /source/src/task.c:1276:19
unknown function (ip: (nil)) at (unknown file)
Allocations: 19898241 (Pool: 19897429; Big: 812); GC: 17

[106] signal 15: Terminated
in expression starting at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/classification/mnist.jl:30
jl_lookup_generic_ at /source/src/gf.c:4489:5
ijl_apply_generic at /source/src/gf.c:4582:35
isbitstype at ./runtime_internals.jl:892:0 (pc: 5)
isbits at ./runtime_internals.jl:899:0 [inlined]
_deepcopy_memory_t at ./deepcopy.jl:119:0 (pc: 108)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_invoke at /source/src/gf.c:4355:12
deepcopy_internal at ./deepcopy.jl:104:0 [inlined]
deepcopy_internal at ./deepcopy.jl:142:0 (pc: 48)
deepcopy_internal at ./deepcopy.jl:133:0 (pc: 65)
unknown function (ip: 0x70d61f5991b6) at (unknown file)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
deepcopy_internal at ./deepcopy.jl:87:0 (pc: 156)
unknown function (ip: 0x70d61f51bc66) at (unknown file)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
deepcopy_internal at ./deepcopy.jl:87:0 (pc: 156)
#deepcopy_internal##0 at ./deepcopy.jl:40:0 [inlined]
ntuple at ./ntuple.jl:19:0 [inlined]
deepcopy_internal at ./deepcopy.jl:39:0 (pc: 3)
unknown function (ip: 0x70d61f5984fc) at (unknown file)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
deepcopy_internal at ./deepcopy.jl:87:0 (pc: 156)
unknown function (ip: 0x70d61f51bc66) at (unknown file)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
_deepcopy_memory_t at ./deepcopy.jl:120:0 (pc: 111)
deepcopy_internal at ./deepcopy.jl:104:0 [inlined]
deepcopy_internal at ./deepcopy.jl:142:0 (pc: 48)
deepcopy_internal at ./deepcopy.jl:133:0 (pc: 65)
deepcopy_internal at ./deepcopy.jl:87:0 [inlined]
deepcopy at ./deepcopy.jl:34:0 [inlined]
#slicedataset#1 at /home/pkgeval/.julia/packages/SoleBase/KRa1C/src/SoleBase.jl:65:0 [inlined]
slicedataset at /home/pkgeval/.julia/packages/SoleBase/KRa1C/src/SoleBase.jl:57:0 [inlined]
#subset#536 at /home/pkgeval/.julia/packages/SoleData/C2yBj/src/types/logiset-MLJ-interface.jl:56:0 [inlined]
subset at /home/pkgeval/.julia/packages/SoleData/C2yBj/src/types/logiset-MLJ-interface.jl:55:0 [inlined]
selectrows at /home/pkgeval/.julia/packages/SoleData/C2yBj/src/types/logiset-MLJ-interface.jl:95:0 [inlined]
selectrows at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/src/interfaces/MLJ.jl:201:0 (pc: 9)
unknown function (ip: 0x70d61f595b7a) at (unknown file)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
jl_apply at /source/src/julia.h:2405:12 [inlined]
jl_f__apply_iterate at /source/src/builtins.c:918:26
#fit_only!#62 at /home/pkgeval/.julia/packages/MLJBase/DCbte/src/machines.jl:677:0 (pc: 101)
fit_only! at /home/pkgeval/.julia/packages/MLJBase/DCbte/src/machines.jl:617:0 [inlined]
#fit!#70 at /home/pkgeval/.julia/packages/MLJBase/DCbte/src/machines.jl:790:0 [inlined]
fit! at /home/pkgeval/.julia/packages/MLJBase/DCbte/src/machines.jl:787:0 [inlined]
|> at ./operators.jl:983:0 (pc: 4)
unknown function (ip: 0x70d61f518cc2) at (unknown file)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
macro expansion at ./timing.jl:741:0 [inlined]
top-level scope at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/classification/mnist.jl:37:0 (pc: 102)
jl_invoke_oneshot at /source/src/gf.c:4383:23
ijl_eval_thunk at /source/src/toplevel.c:756:18
jl_toplevel_eval_flex at /source/src/toplevel.c:708:26
jl_eval_toplevel_stmts at /source/src/toplevel.c:598:15
jl_toplevel_eval_flex at /source/src/toplevel.c:680:27
ijl_toplevel_eval at /source/src/toplevel.c:778:12
ijl_toplevel_eval_in at /source/src/toplevel.c:823:13
eval at ./boot.jl:522:0 (pc: 1)
include_string at ./loading.jl:3132:0 (pc: 190)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
_include at ./loading.jl:3192:0 (pc: 122)
include at ./Base.jl:326:0 (pc: 1)
IncludeInto at ./Base.jl:327:0 [inlined]
run_tests at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:14:0 (pc: 42)
unknown function (ip: 0x70d653f22e72) at (unknown file)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
macro expansion at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55:0 [inlined]
macro expansion at /source/usr/share/julia/stdlib/v1.14/Test/src/Test.jl:2246:0 [inlined]
macro expansion at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:55:0 [inlined]
macro expansion at /source/usr/share/julia/stdlib/v1.14/Test/src/Test.jl:2246:0 [inlined]
top-level scope at /home/pkgeval/.julia/packages/ModalDecisionTrees/d9j23/test/runtests.jl:50:0 (pc: 500)
jl_invoke_oneshot at /source/src/gf.c:4383:23
ijl_eval_thunk at /source/src/toplevel.c:756:18
jl_toplevel_eval_flex at /source/src/toplevel.c:708:26
jl_eval_toplevel_stmts at /source/src/toplevel.c:598:15
jl_toplevel_eval_flex at /source/src/toplevel.c:680:27
ijl_toplevel_eval at /source/src/toplevel.c:778:12
ijl_toplevel_eval_in at /source/src/toplevel.c:823:13
eval at ./boot.jl:522:0 (pc: 1)
include_string at ./loading.jl:3132:0 (pc: 208)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
_include at ./loading.jl:3192:0 (pc: 122)
include at ./Base.jl:326:0 (pc: 1)
IncludeInto at ./Base.jl:327:0 (pc: 2)
jfptr_IncludeInto_1.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
jl_apply at /source/src/julia.h:2405:12 [inlined]
do_call at /source/src/interpreter.c:123:26
eval_value at /source/src/interpreter.c:259:16
eval_stmt_value at /source/src/interpreter.c:194:23 [inlined]
eval_body at /source/src/interpreter.c:757:13
jl_interpret_toplevel_thunk at /source/src/interpreter.c:947:21
ijl_eval_thunk at /source/src/toplevel.c:764:18
jl_toplevel_eval_flex at /source/src/toplevel.c:708:26
jl_eval_toplevel_stmts at /source/src/toplevel.c:598:15
jl_toplevel_eval_flex at /source/src/toplevel.c:680:27
ijl_toplevel_eval at /source/src/toplevel.c:778:12
ijl_toplevel_eval_in at /source/src/toplevel.c:823:13
eval at ./boot.jl:522:0 (pc: 1)
exec_options at ./client.jl:321:0 (pc: 426)
_start at ./client.jl:596:0 (pc: 295)
jfptr__start_0.1 at /opt/julia/lib/julia/sys.so (unknown line)
_jl_invoke at /source/src/gf.c:4348:23 [inlined]
ijl_apply_generic at /source/src/gf.c:4586:12
jl_apply at /source/src/julia.h:2405:12 [inlined]
true_main at /source/src/jlapi.c:985:29
jl_repl_entrypoint at /source/src/jlapi.c:1152:15
main at /source/cli/loader_exe.c:58:15
unknown function (ip: 0x70d66eb14249) at /lib/x86_64-linux-gnu/libc.so.6
__libc_start_main at /lib/x86_64-linux-gnu/libc.so.6 (unknown line)
unknown function (ip: 0x4010b8) at /workspace/srcdir/glibc-2.17/csu/../sysdeps/x86_64/start.S
unknown function (ip: (nil)) at (unknown file)
Allocations: 2085098446 (Pool: 2085069105; Big: 29341); GC: 411

PkgEval terminated after 2723.08s: test duration exceeded the time limit