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1.5.0-DEV-f014071421.log
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Julia Version 1.5.0-DEV.232
Commit f014071421 (2020-02-03 21:36 UTC)
Platform Info:
OS: Linux (x86_64-linux-gnu)
CPU: Intel(R) Xeon(R) Silver 4114 CPU @ 2.20GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-9.0.1 (ORCJIT, skylake)
Environment:
JULIA_DEPOT_PATH = ::/usr/local/share/julia
JULIA_NUM_THREADS = 2
Resolving package versions...
Installed SortingAlgorithms ─────────── v0.3.1
Installed Formatting ────────────────── v0.4.1
Installed RecipesBase ───────────────── v0.7.0
Installed FillArrays ────────────────── v0.8.4
Installed TableTraits ───────────────── v1.0.0
Installed StatsFuns ─────────────────── v0.9.3
Installed ScientificTypes ───────────── v0.5.1
Installed MLJ ───────────────────────── v0.7.0
Installed QuadGK ────────────────────── v2.3.1
Installed DocStringExtensions ───────── v0.8.1
Installed Arpack_jll ────────────────── v3.5.0+2
Installed Requires ──────────────────── v1.0.1
Installed Missings ──────────────────── v0.4.3
Installed ProgressMeter ─────────────── v1.2.0
Installed Rmath ─────────────────────── v0.6.0
Installed ColorTypes ────────────────── v0.8.1
Installed Reexport ──────────────────── v0.2.0
Installed SpecialFunctions ──────────── v0.9.0
Installed DataValueInterfaces ───────── v1.0.0
Installed OpenBLAS_jll ──────────────── v0.3.7+5
Installed InvertedIndices ───────────── v1.0.0
Installed CategoricalArrays ─────────── v0.7.7
Installed JSON ──────────────────────── v0.21.0
Installed LossFunctions ─────────────── v0.5.1
Installed MLJModels ─────────────────── v0.7.2
Installed Distributions ─────────────── v0.21.12
Installed Distances ─────────────────── v0.8.2
Installed Crayons ───────────────────── v4.0.1
Installed StatsBase ─────────────────── v0.32.0
Installed PDMats ────────────────────── v0.9.11
Installed Arpack ────────────────────── v0.4.0
Installed DataAPI ───────────────────── v1.1.0
Installed BinaryProvider ────────────── v0.5.8
Installed Parsers ───────────────────── v0.3.11
Installed MLJBase ───────────────────── v0.10.1
Installed DataStructures ────────────── v0.17.9
Installed LearnBase ─────────────────── v0.2.2
Installed Parameters ────────────────── v0.12.0
Installed PrettyTables ──────────────── v0.6.0
Installed OrderedCollections ────────── v1.1.0
Installed OpenSpecFun_jll ───────────── v0.5.3+1
Installed Tables ────────────────────── v0.2.11
Installed Compat ────────────────────── v2.2.0
Installed IteratorInterfaceExtensions ─ v1.0.0
Installed MultivariateStats ─────────── v0.7.0
Installed ComputationalResources ────── v0.3.0
Installed FixedPointNumbers ─────────── v0.7.1
####### 10.8%######################################################################## 100.0%
#=#=# #### 6.0%############# 18.6%######################### 35.2%######################################## 56.1%################################################################## 92.0%######################################################################## 100.0%
#=#=# ##O#- # ######################################################################## 100.0%
Updating `~/.julia/environments/v1.5/Project.toml`
[add582a8] + MLJ v0.7.0
Updating `~/.julia/environments/v1.5/Manifest.toml`
[7d9fca2a] + Arpack v0.4.0
[68821587] + Arpack_jll v3.5.0+2
[b99e7846] + BinaryProvider v0.5.8
[324d7699] + CategoricalArrays v0.7.7
[3da002f7] + ColorTypes v0.8.1
[34da2185] + Compat v2.2.0
[ed09eef8] + ComputationalResources v0.3.0
[a8cc5b0e] + Crayons v4.0.1
[9a962f9c] + DataAPI v1.1.0
[864edb3b] + DataStructures v0.17.9
[e2d170a0] + DataValueInterfaces v1.0.0
[b4f34e82] + Distances v0.8.2
[31c24e10] + Distributions v0.21.12
[ffbed154] + DocStringExtensions v0.8.1
[1a297f60] + FillArrays v0.8.4
[53c48c17] + FixedPointNumbers v0.7.1
[59287772] + Formatting v0.4.1
[41ab1584] + InvertedIndices v1.0.0
[82899510] + IteratorInterfaceExtensions v1.0.0
[682c06a0] + JSON v0.21.0
[7f8f8fb0] + LearnBase v0.2.2
[30fc2ffe] + LossFunctions v0.5.1
[add582a8] + MLJ v0.7.0
[a7f614a8] + MLJBase v0.10.1
[d491faf4] + MLJModels v0.7.2
[e1d29d7a] + Missings v0.4.3
[6f286f6a] + MultivariateStats v0.7.0
[4536629a] + OpenBLAS_jll v0.3.7+5
[efe28fd5] + OpenSpecFun_jll v0.5.3+1
[bac558e1] + OrderedCollections v1.1.0
[90014a1f] + PDMats v0.9.11
[d96e819e] + Parameters v0.12.0
[69de0a69] + Parsers v0.3.11
[08abe8d2] + PrettyTables v0.6.0
[92933f4c] + ProgressMeter v1.2.0
[1fd47b50] + QuadGK v2.3.1
[3cdcf5f2] + RecipesBase v0.7.0
[189a3867] + Reexport v0.2.0
[ae029012] + Requires v1.0.1
[79098fc4] + Rmath v0.6.0
[321657f4] + ScientificTypes v0.5.1
[a2af1166] + SortingAlgorithms v0.3.1
[276daf66] + SpecialFunctions v0.9.0
[2913bbd2] + StatsBase v0.32.0
[4c63d2b9] + StatsFuns v0.9.3
[3783bdb8] + TableTraits v1.0.0
[bd369af6] + Tables v0.2.11
[2a0f44e3] + Base64
[ade2ca70] + Dates
[8bb1440f] + DelimitedFiles
[8ba89e20] + Distributed
[9fa8497b] + Future
[b77e0a4c] + InteractiveUtils
[76f85450] + LibGit2
[8f399da3] + Libdl
[37e2e46d] + LinearAlgebra
[56ddb016] + Logging
[d6f4376e] + Markdown
[a63ad114] + Mmap
[44cfe95a] + Pkg
[de0858da] + Printf
[3fa0cd96] + REPL
[9a3f8284] + Random
[ea8e919c] + SHA
[9e88b42a] + Serialization
[1a1011a3] + SharedArrays
[6462fe0b] + Sockets
[2f01184e] + SparseArrays
[10745b16] + Statistics
[4607b0f0] + SuiteSparse
[8dfed614] + Test
[cf7118a7] + UUIDs
[4ec0a83e] + Unicode
Building Rmath → `~/.julia/packages/Rmath/BoBag/deps/build.log`
Testing MLJ
#=#=# # 1.7%######################################################################## 100.0%
#=#=# ################# 24.6%######################################################################## 100.0%
#=#=# # 1.8%############### 21.8%################################## 48.5%########################################################### 83.2%######################################################################## 100.0%
Status `/tmp/jl_XUYnlW/Manifest.toml`
[7d9fca2a] Arpack v0.4.0
[68821587] Arpack_jll v3.5.0+2
[b99e7846] BinaryProvider v0.5.8
[336ed68f] CSV v0.5.23
[324d7699] CategoricalArrays v0.7.7
[944b1d66] CodecZlib v0.6.0
[3da002f7] ColorTypes v0.8.1
[34da2185] Compat v2.2.0
[ed09eef8] ComputationalResources v0.3.0
[a8cc5b0e] Crayons v4.0.1
[9a962f9c] DataAPI v1.1.0
[a93c6f00] DataFrames v0.20.0
[864edb3b] DataStructures v0.17.9
[e2d170a0] DataValueInterfaces v1.0.0
[7806a523] DecisionTree v0.10.1
[b4f34e82] Distances v0.8.2
[31c24e10] Distributions v0.21.12
[ffbed154] DocStringExtensions v0.8.1
[e2ba6199] ExprTools v0.1.0
[8f5d6c58] EzXML v1.1.0
[5789e2e9] FileIO v1.2.1
[48062228] FilePathsBase v0.7.0
[1a297f60] FillArrays v0.8.4
[53c48c17] FixedPointNumbers v0.7.1
[59287772] Formatting v0.4.1
[41ab1584] InvertedIndices v1.0.0
[82899510] IteratorInterfaceExtensions v1.0.0
[682c06a0] JSON v0.21.0
[7f8f8fb0] LearnBase v0.2.2
[94ce4f54] Libiconv_jll v1.16.0+1
[30fc2ffe] LossFunctions v0.5.1
[add582a8] MLJ v0.7.0
[a7f614a8] MLJBase v0.10.1
[d491faf4] MLJModels v0.7.2
[e1d29d7a] Missings v0.4.3
[78c3b35d] Mocking v0.7.1
[6f286f6a] MultivariateStats v0.7.0
[b8a86587] NearestNeighbors v0.4.4
[4536629a] OpenBLAS_jll v0.3.7+5
[efe28fd5] OpenSpecFun_jll v0.5.3+1
[bac558e1] OrderedCollections v1.1.0
[90014a1f] PDMats v0.9.11
[d96e819e] Parameters v0.12.0
[69de0a69] Parsers v0.3.11
[2dfb63ee] PooledArrays v0.5.3
[08abe8d2] PrettyTables v0.6.0
[92933f4c] ProgressMeter v1.2.0
[1fd47b50] QuadGK v2.3.1
[df47a6cb] RData v0.6.3
[ce6b1742] RDatasets v0.6.6
[3cdcf5f2] RecipesBase v0.7.0
[189a3867] Reexport v0.2.0
[ae029012] Requires v1.0.1
[79098fc4] Rmath v0.6.0
[321657f4] ScientificTypes v0.5.1
[6e75b9c4] ScikitLearnBase v0.5.0
[a2af1166] SortingAlgorithms v0.3.1
[276daf66] SpecialFunctions v0.9.0
[90137ffa] StaticArrays v0.12.1
[2913bbd2] StatsBase v0.32.0
[4c63d2b9] StatsFuns v0.9.3
[3783bdb8] TableTraits v1.0.0
[bd369af6] Tables v0.2.11
[f269a46b] TimeZones v1.0.0
[3bb67fe8] TranscodingStreams v0.9.5
[b8865327] UnicodePlots v1.1.0
[ea10d353] WeakRefStrings v0.6.2
[02c8fc9c] XML2_jll v2.9.9+1
[83775a58] Zlib_jll v1.2.11+8
[2a0f44e3] Base64
[ade2ca70] Dates
[8bb1440f] DelimitedFiles
[8ba89e20] Distributed
[9fa8497b] Future
[b77e0a4c] InteractiveUtils
[76f85450] LibGit2
[8f399da3] Libdl
[37e2e46d] LinearAlgebra
[56ddb016] Logging
[d6f4376e] Markdown
[a63ad114] Mmap
[44cfe95a] Pkg
[de0858da] Printf
[3fa0cd96] REPL
[9a3f8284] Random
[ea8e919c] SHA
[9e88b42a] Serialization
[1a1011a3] SharedArrays
[6462fe0b] Sockets
[2f01184e] SparseArrays
[10745b16] Statistics
[4607b0f0] SuiteSparse
[8dfed614] Test
[cf7118a7] UUIDs
[4ec0a83e] Unicode
[ Info: Model metadata loaded from registry.
Test Summary: | Pass Total
utilities | 4 4
[ Info: Training [34mMachine{DeterministicTunedModel} @ 1…63[39m.
[ Info: Mimimizing rms.
Iterating over a 40-point grid: 2%[> ] ETA: 0:00:00[KIterating over a 40-point grid: 7%[=> ] ETA: 0:04:46[KIterating over a 40-point grid: 10%[==> ] ETA: 0:03:51[KIterating over a 40-point grid: 12%[===> ] ETA: 0:03:03[KIterating over a 40-point grid: 15%[===> ] ETA: 0:02:31[KIterating over a 40-point grid: 17%[====> ] ETA: 0:02:06[KIterating over a 40-point grid: 20%[====> ] ETA: 0:01:47[KIterating over a 40-point grid: 22%[=====> ] ETA: 0:01:32[KIterating over a 40-point grid: 24%[======> ] ETA: 0:01:20[KIterating over a 40-point grid: 27%[======> ] ETA: 0:01:11[KIterating over a 40-point grid: 29%[=======> ] ETA: 0:01:03[KIterating over a 40-point grid: 32%[=======> ] ETA: 0:00:56[KIterating over a 40-point grid: 34%[========> ] ETA: 0:00:50[KIterating over a 40-point grid: 37%[=========> ] ETA: 0:00:45[KIterating over a 40-point grid: 39%[=========> ] ETA: 0:00:40[KIterating over a 40-point grid: 41%[==========> ] ETA: 0:00:37[KIterating over a 40-point grid: 44%[==========> ] ETA: 0:00:33[KIterating over a 40-point grid: 46%[===========> ] ETA: 0:00:30[KIterating over a 40-point grid: 49%[============> ] ETA: 0:00:27[KIterating over a 40-point grid: 51%[============> ] ETA: 0:00:25[KIterating over a 40-point grid: 54%[=============> ] ETA: 0:00:22[KIterating over a 40-point grid: 56%[==============> ] ETA: 0:00:20[KIterating over a 40-point grid: 59%[==============> ] ETA: 0:00:18[KIterating over a 40-point grid: 61%[===============> ] ETA: 0:00:17[KIterating over a 40-point grid: 63%[===============> ] ETA: 0:00:15[KIterating over a 40-point grid: 66%[================> ] ETA: 0:00:13[KIterating over a 40-point grid: 68%[=================> ] ETA: 0:00:12[KIterating over a 40-point grid: 71%[=================> ] ETA: 0:00:11[KIterating over a 40-point grid: 73%[==================> ] ETA: 0:00:09[KIterating over a 40-point grid: 76%[==================> ] ETA: 0:00:08[KIterating over a 40-point grid: 78%[===================> ] ETA: 0:00:07[KIterating over a 40-point grid: 80%[====================> ] ETA: 0:00:06[KIterating over a 40-point grid: 83%[====================> ] ETA: 0:00:05[KIterating over a 40-point grid: 85%[=====================> ] ETA: 0:00:04[KIterating over a 40-point grid: 88%[=====================> ] ETA: 0:00:04[KIterating over a 40-point grid: 90%[======================> ] ETA: 0:00:03[KIterating over a 40-point grid: 93%[=======================> ] ETA: 0:00:02[KIterating over a 40-point grid: 95%[=======================> ] ETA: 0:00:01[KIterating over a 40-point grid: 98%[========================>] ETA: 0:00:01[KIterating over a 40-point grid: 100%[=========================] Time: 0:00:25[K
[ Info: Training best model on all supplied data.
[ Info: Updating [34mMachine{DeterministicTunedModel} @ 1…63[39m.
[ Info: Mimimizing rms.
Iterating over a 40-point grid: 2%[> ] ETA: 0:00:00[KIterating over a 40-point grid: 7%[=> ] ETA: 0:00:00[KIterating over a 40-point grid: 10%[==> ] ETA: 0:00:00[KIterating over a 40-point grid: 12%[===> ] ETA: 0:00:00[KIterating over a 40-point grid: 15%[===> ] ETA: 0:00:00[KIterating over a 40-point grid: 17%[====> ] ETA: 0:00:00[KIterating over a 40-point grid: 20%[====> ] ETA: 0:00:00[KIterating over a 40-point grid: 22%[=====> ] ETA: 0:00:00[KIterating over a 40-point grid: 24%[======> ] ETA: 0:00:00[KIterating over a 40-point grid: 27%[======> ] ETA: 0:00:00[KIterating over a 40-point grid: 29%[=======> ] ETA: 0:00:00[KIterating over a 40-point grid: 32%[=======> ] ETA: 0:00:00[KIterating over a 40-point grid: 34%[========> ] ETA: 0:00:00[KIterating over a 40-point grid: 37%[=========> ] ETA: 0:00:00[KIterating over a 40-point grid: 39%[=========> ] ETA: 0:00:00[KIterating over a 40-point grid: 41%[==========> ] ETA: 0:00:00[KIterating over a 40-point grid: 44%[==========> ] ETA: 0:00:00[KIterating over a 40-point grid: 46%[===========> ] ETA: 0:00:00[KIterating over a 40-point grid: 49%[============> ] ETA: 0:00:00[KIterating over a 40-point grid: 51%[============> ] ETA: 0:00:00[KIterating over a 40-point grid: 54%[=============> ] ETA: 0:00:00[KIterating over a 40-point grid: 56%[==============> ] ETA: 0:00:00[KIterating over a 40-point grid: 59%[==============> ] ETA: 0:00:00[KIterating over a 40-point grid: 61%[===============> ] ETA: 0:00:00[KIterating over a 40-point grid: 63%[===============> ] ETA: 0:00:00[KIterating over a 40-point grid: 66%[================> ] ETA: 0:00:00[KIterating over a 40-point grid: 68%[=================> ] ETA: 0:00:00[KIterating over a 40-point grid: 71%[=================> ] ETA: 0:00:00[KIterating over a 40-point grid: 73%[==================> ] ETA: 0:00:00[KIterating over a 40-point grid: 76%[==================> ] ETA: 0:00:00[KIterating over a 40-point grid: 78%[===================> ] ETA: 0:00:00[KIterating over a 40-point grid: 80%[====================> ] ETA: 0:00:00[KIterating over a 40-point grid: 83%[====================> ] ETA: 0:00:00[KIterating over a 40-point grid: 85%[=====================> ] ETA: 0:00:00[KIterating over a 40-point grid: 88%[=====================> ] ETA: 0:00:00[KIterating over a 40-point grid: 90%[======================> ] ETA: 0:00:00[KIterating over a 40-point grid: 93%[=======================> ] ETA: 0:00:00[KIterating over a 40-point grid: 95%[=======================> ] ETA: 0:00:00[KIterating over a 40-point grid: 98%[========================>] ETA: 0:00:00[KIterating over a 40-point grid: 100%[=========================] Time: 0:00:00[K
[ Info: Training best model on all supplied data.
[ Info: Updating [34mMachine{DeterministicTunedModel} @ 1…63[39m.
[ Info: Mimimizing rms.
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[ Info: Training best model on all supplied data.
┌ Info: A model type "KNNRegressor" is already loaded.
└ No new code loaded.
[ Info: Training [34mMachine{DeterministicTunedModel} @ 8…26[39m.
[ Info: Mimimizing rms.
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[ Info: Training best model on all supplied data.
[ Info: Updating [34mMachine{DeterministicTunedModel} @ 8…26[39m.
[ Info: Mimimizing rms.
Iterating over a 56-point grid: 2%[> ] ETA: 0:00:00[KIterating over a 56-point grid: 5%[=> ] ETA: 0:00:01[KIterating over a 56-point grid: 7%[=> ] ETA: 0:00:01[KIterating over a 56-point grid: 9%[==> ] ETA: 0:00:01[KIterating over a 56-point grid: 11%[==> ] ETA: 0:00:01[KIterating over a 56-point grid: 12%[===> ] ETA: 0:00:01[KIterating over a 56-point grid: 14%[===> ] ETA: 0:00:01[KIterating over a 56-point grid: 16%[===> ] ETA: 0:00:01[KIterating over a 56-point grid: 18%[====> ] ETA: 0:00:01[KIterating over a 56-point grid: 19%[====> ] ETA: 0:00:01[KIterating over a 56-point grid: 21%[=====> ] ETA: 0:00:01[KIterating over a 56-point grid: 23%[=====> ] ETA: 0:00:01[KIterating over a 56-point grid: 25%[======> ] ETA: 0:00:01[KIterating over a 56-point grid: 26%[======> ] ETA: 0:00:01[KIterating over a 56-point grid: 28%[=======> ] ETA: 0:00:01[KIterating over a 56-point grid: 30%[=======> ] ETA: 0:00:01[KIterating over a 56-point grid: 32%[=======> ] ETA: 0:00:01[KIterating over a 56-point grid: 33%[========> ] ETA: 0:00:01[KIterating over a 56-point grid: 35%[========> ] ETA: 0:00:01[KIterating over a 56-point grid: 37%[=========> ] ETA: 0:00:01[KIterating over a 56-point grid: 39%[=========> ] ETA: 0:00:01[KIterating over a 56-point grid: 40%[==========> ] ETA: 0:00:01[KIterating over a 56-point grid: 42%[==========> ] ETA: 0:00:01[KIterating over a 56-point grid: 44%[==========> ] ETA: 0:00:01[KIterating over a 56-point grid: 46%[===========> ] ETA: 0:00:01[KIterating over a 56-point grid: 47%[===========> ] ETA: 0:00:01[KIterating over a 56-point grid: 49%[============> ] ETA: 0:00:01[KIterating over a 56-point grid: 51%[============> ] ETA: 0:00:01[KIterating over a 56-point grid: 53%[=============> ] ETA: 0:00:01[KIterating over a 56-point grid: 54%[=============> ] ETA: 0:00:01[KIterating over a 56-point grid: 56%[==============> ] ETA: 0:00:01[KIterating over a 56-point grid: 58%[==============> ] ETA: 0:00:01[KIterating over a 56-point grid: 60%[==============> ] ETA: 0:00:01[KIterating over a 56-point grid: 61%[===============> ] ETA: 0:00:01[KIterating over a 56-point grid: 63%[===============> ] ETA: 0:00:01[KIterating over a 56-point grid: 65%[================> ] ETA: 0:00:01[KIterating over a 56-point grid: 67%[================> ] ETA: 0:00:01[KIterating over a 56-point grid: 68%[=================> ] ETA: 0:00:01[KIterating over a 56-point grid: 70%[=================> ] ETA: 0:00:01[KIterating over a 56-point grid: 72%[=================> ] ETA: 0:00:01[KIterating over a 56-point grid: 74%[==================> ] ETA: 0:00:01[KIterating over a 56-point grid: 75%[==================> ] ETA: 0:00:01[KIterating over a 56-point grid: 77%[===================> ] ETA: 0:00:00[KIterating over a 56-point grid: 79%[===================> ] ETA: 0:00:00[KIterating over a 56-point grid: 81%[====================> ] ETA: 0:00:00[KIterating over a 56-point grid: 82%[====================> ] ETA: 0:00:00[KIterating over a 56-point grid: 84%[=====================> ] ETA: 0:00:00[KIterating over a 56-point grid: 86%[=====================> ] ETA: 0:00:00[KIterating over a 56-point grid: 88%[=====================> ] ETA: 0:00:00[KIterating over a 56-point grid: 89%[======================> ] ETA: 0:00:00[KIterating over a 56-point grid: 91%[======================> ] ETA: 0:00:00[KIterating over a 56-point grid: 93%[=======================> ] ETA: 0:00:00[KIterating over a 56-point grid: 95%[=======================> ] ETA: 0:00:00[KIterating over a 56-point grid: 96%[========================>] ETA: 0:00:00[KIterating over a 56-point grid: 98%[========================>] ETA: 0:00:00[KIterating over a 56-point grid: 100%[=========================] Time: 0:00:02[K
[ Info: Training best model on all supplied data.
[ Info: Updating [34mMachine{DeterministicTunedModel} @ 8…26[39m.
┌ Warning: No resolution specified for forest.bagging_fraction. Will use a value of 5.
└ @ MLJ ~/.julia/packages/MLJ/YWvn8/src/tuning.jl:202
[ Info: Mimimizing rms.
Iterating over a 60-point grid: 2%[> ] ETA: 0:00:00[KIterating over a 60-point grid: 5%[=> ] ETA: 0:00:01[KIterating over a 60-point grid: 7%[=> ] ETA: 0:00:01[KIterating over a 60-point grid: 8%[==> ] ETA: 0:00:01[KIterating over a 60-point grid: 10%[==> ] ETA: 0:00:01[KIterating over a 60-point grid: 11%[==> ] ETA: 0:00:01[KIterating over a 60-point grid: 13%[===> ] ETA: 0:00:01[KIterating over a 60-point grid: 15%[===> ] ETA: 0:00:01[KIterating over a 60-point grid: 16%[====> ] ETA: 0:00:01[KIterating over a 60-point grid: 18%[====> ] ETA: 0:00:01[KIterating over a 60-point grid: 20%[====> ] ETA: 0:00:01[KIterating over a 60-point grid: 21%[=====> ] ETA: 0:00:01[KIterating over a 60-point grid: 23%[=====> ] ETA: 0:00:01[KIterating over a 60-point grid: 25%[======> ] ETA: 0:00:01[KIterating over a 60-point grid: 26%[======> ] ETA: 0:00:01[KIterating over a 60-point grid: 28%[======> ] ETA: 0:00:01[KIterating over a 60-point grid: 30%[=======> ] ETA: 0:00:01[KIterating over a 60-point grid: 31%[=======> ] ETA: 0:00:01[KIterating over a 60-point grid: 33%[========> ] ETA: 0:00:01[KIterating over a 60-point grid: 34%[========> ] ETA: 0:00:01[KIterating over a 60-point grid: 36%[=========> ] ETA: 0:00:01[KIterating over a 60-point grid: 38%[=========> ] ETA: 0:00:01[KIterating over a 60-point grid: 39%[=========> ] ETA: 0:00:01[KIterating over a 60-point grid: 41%[==========> ] ETA: 0:00:01[KIterating over a 60-point grid: 43%[==========> ] ETA: 0:00:01[KIterating over a 60-point grid: 44%[===========> ] ETA: 0:00:01[KIterating over a 60-point grid: 46%[===========> ] ETA: 0:00:01[KIterating over a 60-point grid: 48%[===========> ] ETA: 0:00:01[KIterating over a 60-point grid: 49%[============> ] ETA: 0:00:01[KIterating over a 60-point grid: 51%[============> ] ETA: 0:00:01[KIterating over a 60-point grid: 52%[=============> ] ETA: 0:00:01[KIterating over a 60-point grid: 54%[=============> ] ETA: 0:00:01[KIterating over a 60-point grid: 56%[=============> ] ETA: 0:00:01[KIterating over a 60-point grid: 57%[==============> ] ETA: 0:00:01[KIterating over a 60-point grid: 59%[==============> ] ETA: 0:00:01[KIterating over a 60-point grid: 61%[===============> ] ETA: 0:00:01[KIterating over a 60-point grid: 62%[===============> ] ETA: 0:00:01[KIterating over a 60-point grid: 64%[===============> ] ETA: 0:00:01[KIterating over a 60-point grid: 66%[================> ] ETA: 0:00:01[KIterating over a 60-point grid: 67%[================> ] ETA: 0:00:01[KIterating over a 60-point grid: 69%[=================> ] ETA: 0:00:01[KIterating over a 60-point grid: 70%[=================> ] ETA: 0:00:01[KIterating over a 60-point grid: 72%[==================> ] ETA: 0:00:01[KIterating over a 60-point grid: 74%[==================> ] ETA: 0:00:01[KIterating over a 60-point grid: 75%[==================> ] ETA: 0:00:00[KIterating over a 60-point grid: 77%[===================> ] ETA: 0:00:00[KIterating over a 60-point grid: 79%[===================> ] ETA: 0:00:00[KIterating over a 60-point grid: 80%[====================> ] ETA: 0:00:00[KIterating over a 60-point grid: 82%[====================> ] ETA: 0:00:00[KIterating over a 60-point grid: 84%[====================> ] ETA: 0:00:00[KIterating over a 60-point grid: 85%[=====================> ] ETA: 0:00:00[KIterating over a 60-point grid: 87%[=====================> ] ETA: 0:00:00[KIterating over a 60-point grid: 89%[======================> ] ETA: 0:00:00[KIterating over a 60-point grid: 90%[======================> ] ETA: 0:00:00[KIterating over a 60-point grid: 92%[======================> ] ETA: 0:00:00[KIterating over a 60-point grid: 93%[=======================> ] ETA: 0:00:00[KIterating over a 60-point grid: 95%[=======================> ] ETA: 0:00:00[KIterating over a 60-point grid: 97%[========================>] ETA: 0:00:00[KIterating over a 60-point grid: 98%[========================>] ETA: 0:00:00[KIterating over a 60-point grid: 100%[=========================] Time: 0:00:01[K
[ Info: Training best model on all supplied data.
┌ Warning: No measure specified. Setting measure=rms.
└ @ MLJBase ~/.julia/packages/MLJBase/t7MaX/src/machines.jl:155
[ Info: Training [34mMachine{DeterministicTunedModel} @ 8…24[39m.
[ Info: Mimimizing rms.
Iterating over a 10-point grid: 9%[==> ] ETA: 0:00:00[KIterating over a 10-point grid: 27%[======> ] ETA: 0:00:04[KIterating over a 10-point grid: 36%[=========> ] ETA: 0:00:03[KIterating over a 10-point grid: 45%[===========> ] ETA: 0:00:02[KIterating over a 10-point grid: 55%[=============> ] ETA: 0:00:01[KIterating over a 10-point grid: 64%[===============> ] ETA: 0:00:01[KIterating over a 10-point grid: 73%[==================> ] ETA: 0:00:01[KIterating over a 10-point grid: 82%[====================> ] ETA: 0:00:00[KIterating over a 10-point grid: 91%[======================> ] ETA: 0:00:00[KIterating over a 10-point grid: 100%[=========================] Time: 0:00:01[K
[ Info: Training best model on all supplied data.
[ Info: Training [34mMachine{DeterministicTunedModel} @ 8…18[39m.
[ Info: Mimimizing rms.
atom.K=3 bagging_fraction=0.4 measurement=0.2973770670340338
atom.K=4 bagging_fraction=0.4 measurement=0.29487431347616055
atom.K=3 bagging_fraction=0.7 measurement=0.3053084971552806
atom.K=4 bagging_fraction=0.7 measurement=0.3007352876810562
atom.K=3 bagging_fraction=1.0 measurement=0.322315125056536
atom.K=4 bagging_fraction=1.0 measurement=0.31259942522260187
[ Info: Training best model on all supplied data.
[ Info: Training [34mMachine{DeterministicEnsembleModel{KNNRegressor}} @ 1…71[39m.
[ Info: Training [34mMachine{ProbabilisticTunedModel} @ 1…13[39m.
[ Info: Maximizing BrierScore(UnivariateFinite).
Iterating over a 10-point grid: 9%[==> ] ETA: 0:00:00[KIterating over a 10-point grid: 27%[======> ] ETA: 0:00:21[KIterating over a 10-point grid: 36%[=========> ] ETA: 0:00:14[KIterating over a 10-point grid: 45%[===========> ] ETA: 0:00:10[KIterating over a 10-point grid: 55%[=============> ] ETA: 0:00:07[KIterating over a 10-point grid: 64%[===============> ] ETA: 0:00:05[KIterating over a 10-point grid: 73%[==================> ] ETA: 0:00:03[KIterating over a 10-point grid: 82%[====================> ] ETA: 0:00:02[KIterating over a 10-point grid: 91%[======================> ] ETA: 0:00:01[KIterating over a 10-point grid: 100%[=========================] Time: 0:00:08[K
[ Info: Training best model on all supplied data.
[ Info: Training [34mMachine{ProbabilisticTunedModel} @ 1…30[39m.
[ Info: Maximizing BrierScore(UnivariateFinite).
Iterating over a 10-point grid: 9%[==> ] ETA: 0:00:00[KIterating over a 10-point grid: 27%[======> ] ETA: 0:00:03[KIterating over a 10-point grid: 36%[=========> ] ETA: 0:00:02[KIterating over a 10-point grid: 45%[===========> ] ETA: 0:00:01[KIterating over a 10-point grid: 55%[=============> ] ETA: 0:00:01[KIterating over a 10-point grid: 64%[===============> ] ETA: 0:00:01[KIterating over a 10-point grid: 73%[==================> ] ETA: 0:00:00[KIterating over a 10-point grid: 82%[====================> ] ETA: 0:00:00[KIterating over a 10-point grid: 91%[======================> ] ETA: 0:00:00[KIterating over a 10-point grid: 100%[=========================] Time: 0:00:01[K
[ Info: Training best model on all supplied data.
[ Info: Training [34mMachine{ProbabilisticTunedModel} @ 1…31[39m.
[ Info: Maximizing BrierScore(UnivariateFinite).
Iterating over a 10-point grid: 9%[==> ] ETA: 0:00:00[KIterating over a 10-point grid: 27%[======> ] ETA: 0:00:00[KIterating over a 10-point grid: 36%[=========> ] ETA: 0:00:00[KIterating over a 10-point grid: 45%[===========> ] ETA: 0:00:00[KIterating over a 10-point grid: 55%[=============> ] ETA: 0:00:00[KIterating over a 10-point grid: 64%[===============> ] ETA: 0:00:00[KIterating over a 10-point grid: 73%[==================> ] ETA: 0:00:00[KIterating over a 10-point grid: 82%[====================> ] ETA: 0:00:00[KIterating over a 10-point grid: 91%[======================> ] ETA: 0:00:00[KIterating over a 10-point grid: 100%[=========================] Time: 0:00:00[K
[ Info: Training best model on all supplied data.
[ Info: No measure specified. Using measure=rms.
[ Info: Training [34mMachine{DeterministicTunedModel} @ 1…70[39m.
Iterating over a 30-point grid: 3%[> ] ETA: 0:00:00[KIterating over a 30-point grid: 10%[==> ] ETA: 0:00:28[KIterating over a 30-point grid: 13%[===> ] ETA: 0:00:24[KIterating over a 30-point grid: 16%[====> ] ETA: 0:00:19[KIterating over a 30-point grid: 19%[====> ] ETA: 0:00:15[KIterating over a 30-point grid: 23%[=====> ] ETA: 0:00:12[KIterating over a 30-point grid: 26%[======> ] ETA: 0:00:10[KIterating over a 30-point grid: 29%[=======> ] ETA: 0:00:09[KIterating over a 30-point grid: 32%[========> ] ETA: 0:00:08[KIterating over a 30-point grid: 35%[========> ] ETA: 0:00:07[KIterating over a 30-point grid: 39%[=========> ] ETA: 0:00:06[KIterating over a 30-point grid: 42%[==========> ] ETA: 0:00:05[KIterating over a 30-point grid: 45%[===========> ] ETA: 0:00:04[KIterating over a 30-point grid: 48%[============> ] ETA: 0:00:04[KIterating over a 30-point grid: 52%[============> ] ETA: 0:00:03[KIterating over a 30-point grid: 55%[=============> ] ETA: 0:00:03[KIterating over a 30-point grid: 58%[==============> ] ETA: 0:00:03[KIterating over a 30-point grid: 61%[===============> ] ETA: 0:00:02[KIterating over a 30-point grid: 65%[================> ] ETA: 0:00:02[KIterating over a 30-point grid: 68%[================> ] ETA: 0:00:02[KIterating over a 30-point grid: 71%[=================> ] ETA: 0:00:02[KIterating over a 30-point grid: 74%[==================> ] ETA: 0:00:01[KIterating over a 30-point grid: 77%[===================> ] ETA: 0:00:01[KIterating over a 30-point grid: 81%[====================> ] ETA: 0:00:01[KIterating over a 30-point grid: 84%[====================> ] ETA: 0:00:01[KIterating over a 30-point grid: 87%[=====================> ] ETA: 0:00:01[KIterating over a 30-point grid: 90%[======================> ] ETA: 0:00:00[KIterating over a 30-point grid: 94%[=======================> ] ETA: 0:00:00[KIterating over a 30-point grid: 97%[========================>] ETA: 0:00:00[KIterating over a 30-point grid: 100%[=========================] Time: 0:00:03[K
┌ Info: Training of best model suppressed.
└ To train tuning machine `mach` on all supplied data, call `fit!(mach.fitresult)`.
[ Info: No measure specified. Using measure=rms.
[ Info: Training [34mMachine{DeterministicTunedModel} @ 7…08[39m.
Iterating over a 30-point grid: 3%[> ] ETA: 0:00:00[KIterating over a 30-point grid: 10%[==> ] ETA: 0:00:00[KIterating over a 30-point grid: 13%[===> ] ETA: 0:00:00[KIterating over a 30-point grid: 16%[====> ] ETA: 0:00:00[KIterating over a 30-point grid: 19%[====> ] ETA: 0:00:00[KIterating over a 30-point grid: 23%[=====> ] ETA: 0:00:00[KIterating over a 30-point grid: 26%[======> ] ETA: 0:00:00[KIterating over a 30-point grid: 29%[=======> ] ETA: 0:00:00[KIterating over a 30-point grid: 32%[========> ] ETA: 0:00:00[KIterating over a 30-point grid: 35%[========> ] ETA: 0:00:00[KIterating over a 30-point grid: 39%[=========> ] ETA: 0:00:00[KIterating over a 30-point grid: 42%[==========> ] ETA: 0:00:00[KIterating over a 30-point grid: 45%[===========> ] ETA: 0:00:00[KIterating over a 30-point grid: 48%[============> ] ETA: 0:00:00[KIterating over a 30-point grid: 52%[============> ] ETA: 0:00:00[KIterating over a 30-point grid: 55%[=============> ] ETA: 0:00:00[KIterating over a 30-point grid: 58%[==============> ] ETA: 0:00:00[KIterating over a 30-point grid: 61%[===============> ] ETA: 0:00:00[KIterating over a 30-point grid: 65%[================> ] ETA: 0:00:00[KIterating over a 30-point grid: 68%[================> ] ETA: 0:00:00[KIterating over a 30-point grid: 71%[=================> ] ETA: 0:00:00[KIterating over a 30-point grid: 74%[==================> ] ETA: 0:00:00[KIterating over a 30-point grid: 77%[===================> ] ETA: 0:00:00[KIterating over a 30-point grid: 81%[====================> ] ETA: 0:00:00[KIterating over a 30-point grid: 84%[====================> ] ETA: 0:00:00[KIterating over a 30-point grid: 87%[=====================> ] ETA: 0:00:00[KIterating over a 30-point grid: 90%[======================> ] ETA: 0:00:00[KIterating over a 30-point grid: 94%[=======================> ] ETA: 0:00:00[KIterating over a 30-point grid: 97%[========================>] ETA: 0:00:00[KIterating over a 30-point grid: 100%[=========================] Time: 0:00:00[K
┌ Info: Training of best model suppressed.
└ To train tuning machine `mach` on all supplied data, call `fit!(mach.fitresult)`.
[ Info: No measure specified. Using measure=rms.
[ Info: Training [34mMachine{DeterministicTunedModel} @ 1…64[39m.
Iterating over a 30-point grid: 3%[> ] ETA: 0:00:00[KIterating over a 30-point grid: 10%[==> ] ETA: 0:00:00[KIterating over a 30-point grid: 13%[===> ] ETA: 0:00:00[KIterating over a 30-point grid: 16%[====> ] ETA: 0:00:00[KIterating over a 30-point grid: 19%[====> ] ETA: 0:00:00[KIterating over a 30-point grid: 23%[=====> ] ETA: 0:00:00[KIterating over a 30-point grid: 26%[======> ] ETA: 0:00:00[KIterating over a 30-point grid: 29%[=======> ] ETA: 0:00:00[KIterating over a 30-point grid: 32%[========> ] ETA: 0:00:00[KIterating over a 30-point grid: 35%[========> ] ETA: 0:00:00[KIterating over a 30-point grid: 39%[=========> ] ETA: 0:00:00[KIterating over a 30-point grid: 42%[==========> ] ETA: 0:00:00[KIterating over a 30-point grid: 45%[===========> ] ETA: 0:00:00[KIterating over a 30-point grid: 48%[============> ] ETA: 0:00:00[KIterating over a 30-point grid: 52%[============> ] ETA: 0:00:00[KIterating over a 30-point grid: 55%[=============> ] ETA: 0:00:00[KIterating over a 30-point grid: 58%[==============> ] ETA: 0:00:00[KIterating over a 30-point grid: 61%[===============> ] ETA: 0:00:00[KIterating over a 30-point grid: 65%[================> ] ETA: 0:00:00[KIterating over a 30-point grid: 68%[================> ] ETA: 0:00:00[KIterating over a 30-point grid: 71%[=================> ] ETA: 0:00:00[KIterating over a 30-point grid: 74%[==================> ] ETA: 0:00:00[KIterating over a 30-point grid: 77%[===================> ] ETA: 0:00:00[KIterating over a 30-point grid: 81%[====================> ] ETA: 0:00:00[KIterating over a 30-point grid: 84%[====================> ] ETA: 0:00:00[KIterating over a 30-point grid: 87%[=====================> ] ETA: 0:00:00[KIterating over a 30-point grid: 90%[======================> ] ETA: 0:00:00[KIterating over a 30-point grid: 94%[=======================> ] ETA: 0:00:00[KIterating over a 30-point grid: 97%[========================>] ETA: 0:00:00[KIterating over a 30-point grid: 100%[=========================] Time: 0:00:00[K
┌ Info: Training of best model suppressed.
└ To train tuning machine `mach` on all supplied data, call `fit!(mach.fitresult)`.
Test Summary: | Pass Total
tuning | 19 19
Iterating over a 30-point grid: 3%[> ] ETA: 0:00:00[KIterating over a 30-point grid: 10%[==> ] ETA: 0:00:23[KIterating over a 30-point grid: 13%[===> ] ETA: 0:00:22[KIterating over a 30-point grid: 16%[====> ] ETA: 0:00:17[KIterating over a 30-point grid: 19%[====> ] ETA: 0:00:13[KIterating over a 30-point grid: 23%[=====> ] ETA: 0:00:11[KIterating over a 30-point grid: 26%[======> ] ETA: 0:00:09[KIterating over a 30-point grid: 29%[=======> ] ETA: 0:00:08[KIterating over a 30-point grid: 32%[========> ] ETA: 0:00:07[KIterating over a 30-point grid: 35%[========> ] ETA: 0:00:06[KIterating over a 30-point grid: 39%[=========> ] ETA: 0:00:05[KIterating over a 30-point grid: 42%[==========> ] ETA: 0:00:04[KIterating over a 30-point grid: 45%[===========> ] ETA: 0:00:04[KIterating over a 30-point grid: 48%[============> ] ETA: 0:00:03[KIterating over a 30-point grid: 52%[============> ] ETA: 0:00:03[KIterating over a 30-point grid: 55%[=============> ] ETA: 0:00:03[KIterating over a 30-point grid: 58%[==============> ] ETA: 0:00:02[KIterating over a 30-point grid: 61%[===============> ] ETA: 0:00:02[KIterating over a 30-point grid: 65%[================> ] ETA: 0:00:02[KIterating over a 30-point grid: 68%[================> ] ETA: 0:00:02[KIterating over a 30-point grid: 71%[=================> ] ETA: 0:00:01[KIterating over a 30-point grid: 74%[==================> ] ETA: 0:00:01[KIterating over a 30-point grid: 77%[===================> ] ETA: 0:00:01[KIterating over a 30-point grid: 81%[====================> ] ETA: 0:00:01[KIterating over a 30-point grid: 84%[====================> ] ETA: 0:00:01[KIterating over a 30-point grid: 87%[=====================> ] ETA: 0:00:00[KIterating over a 30-point grid: 90%[======================> ] ETA: 0:00:00[KIterating over a 30-point grid: 94%[=======================> ] ETA: 0:00:00[KIterating over a 30-point grid: 97%[========================>] ETA: 0:00:00[KIterating over a 30-point grid: 100%[=========================] Time: 0:00:03[K
[ Info: No measure specified. Using measure=rms.
[ Info: Training [34mMachine{DeterministicTunedModel} @ 4…68[39m.
Iterating over a 30-point grid: 3%[> ] ETA: 0:00:00[KIterating over a 30-point grid: 10%[==> ] ETA: 0:00:00[KIterating over a 30-point grid: 13%[===> ] ETA: 0:00:00[KIterating over a 30-point grid: 16%[====> ] ETA: 0:00:00[KIterating over a 30-point grid: 19%[====> ] ETA: 0:00:00[KIterating over a 30-point grid: 23%[=====> ] ETA: 0:00:00[KIterating over a 30-point grid: 26%[======> ] ETA: 0:00:00[KIterating over a 30-point grid: 29%[=======> ] ETA: 0:00:00[KIterating over a 30-point grid: 32%[========> ] ETA: 0:00:00[KIterating over a 30-point grid: 35%[========> ] ETA: 0:00:00[KIterating over a 30-point grid: 39%[=========> ] ETA: 0:00:00[KIterating over a 30-point grid: 42%[==========> ] ETA: 0:00:00[KIterating over a 30-point grid: 45%[===========> ] ETA: 0:00:00[KIterating over a 30-point grid: 48%[============> ] ETA: 0:00:00[KIterating over a 30-point grid: 52%[============> ] ETA: 0:00:00[KIterating over a 30-point grid: 55%[=============> ] ETA: 0:00:00[KIterating over a 30-point grid: 58%[==============> ] ETA: 0:00:00[KIterating over a 30-point grid: 61%[===============> ] ETA: 0:00:00[KIterating over a 30-point grid: 65%[================> ] ETA: 0:00:00[KIterating over a 30-point grid: 68%[================> ] ETA: 0:00:00[KIterating over a 30-point grid: 71%[=================> ] ETA: 0:00:00[KIterating over a 30-point grid: 74%[==================> ] ETA: 0:00:00[KIterating over a 30-point grid: 77%[===================> ] ETA: 0:00:00[KIterating over a 30-point grid: 81%[====================> ] ETA: 0:00:00[KIterating over a 30-point grid: 84%[====================> ] ETA: 0:00:00[KIterating over a 30-point grid: 87%[=====================> ] ETA: 0:00:00[KIterating over a 30-point grid: 90%[======================> ] ETA: 0:00:00[KIterating over a 30-point grid: 94%[=======================> ] ETA: 0:00:00[KIterating over a 30-point grid: 97%[========================>] ETA: 0:00:00[KIterating over a 30-point grid: 100%[=========================] Time: 0:00:00[K
┌ Info: Training of best model suppressed.
└ To train tuning machine `mach` on all supplied data, call `fit!(mach.fitresult)`.
[ Info: No measure specified. Using measure=rms.
[ Info: Training [34mMachine{DeterministicTunedModel} @ 1…09[39m.
Iterating over a 30-point grid: 3%[> ] ETA: 0:00:00[KIterating over a 30-point grid: 10%[==> ] ETA: 0:00:00[KIterating over a 30-point grid: 13%[===> ] ETA: 0:00:00[KIterating over a 30-point grid: 16%[====> ] ETA: 0:00:00[KIterating over a 30-point grid: 19%[====> ] ETA: 0:00:00[KIterating over a 30-point grid: 23%[=====> ] ETA: 0:00:00[KIterating over a 30-point grid: 26%[======> ] ETA: 0:00:00[KIterating over a 30-point grid: 29%[=======> ] ETA: 0:00:00[KIterating over a 30-point grid: 32%[========> ] ETA: 0:00:00[KIterating over a 30-point grid: 35%[========> ] ETA: 0:00:00[KIterating over a 30-point grid: 39%[=========> ] ETA: 0:00:00[KIterating over a 30-point grid: 42%[==========> ] ETA: 0:00:00[KIterating over a 30-point grid: 45%[===========> ] ETA: 0:00:00[KIterating over a 30-point grid: 48%[============> ] ETA: 0:00:00[KIterating over a 30-point grid: 52%[============> ] ETA: 0:00:00[KIterating over a 30-point grid: 55%[=============> ] ETA: 0:00:00[KIterating over a 30-point grid: 58%[==============> ] ETA: 0:00:00[KIterating over a 30-point grid: 61%[===============> ] ETA: 0:00:00[KIterating over a 30-point grid: 65%[================> ] ETA: 0:00:00[KIterating over a 30-point grid: 68%[================> ] ETA: 0:00:00[KIterating over a 30-point grid: 71%[=================> ] ETA: 0:00:00[KIterating over a 30-point grid: 74%[==================> ] ETA: 0:00:00[KIterating over a 30-point grid: 77%[===================> ] ETA: 0:00:00[KIterating over a 30-point grid: 81%[====================> ] ETA: 0:00:00[KIterating over a 30-point grid: 84%[====================> ] ETA: 0:00:00[KIterating over a 30-point grid: 87%[=====================> ] ETA: 0:00:00[KIterating over a 30-point grid: 90%[======================> ] ETA: 0:00:00[KIterating over a 30-point grid: 94%[=======================> ] ETA: 0:00:00[KIterating over a 30-point grid: 97%[========================>] ETA: 0:00:00[KIterating over a 30-point grid: 100%[=========================] Time: 0:00:00[K
┌ Info: Training of best model suppressed.
└ To train tuning machine `mach` on all supplied data, call `fit!(mach.fitresult)`.
Test Summary: | Pass Total
learning_curves | 3 3
Training ensemble: 20%[==========> ] ETA: 0:00:03[KTraining ensemble: 100%[==================================================] Time: 0:00:00[K
Training ensemble: 20%[==========> ] ETA: 0:00:04[KTraining ensemble: 100%[==================================================] Time: 0:00:01[K
Training ensemble: 20%[==========> ] ETA: 0:00:05[KTraining ensemble: 100%[==================================================] Time: 0:00:01[K
[ Info: Training [34mMachine{DeterministicEnsembleModel{KNNRegressor}} @ 6…94[39m.
Training ensemble: 2%[=> ] ETA: 0:00:44[KTraining ensemble: 100%[==================================================] Time: 0:00:00[K
Test Summary: | Pass Total
ensembles | 43 43
Test Summary: | Pass Total
matching models to data | 11 11
┌ Warning: SupervisedTask is deprecated. For model search options, see https://alan-turing-institute.github.io/MLJ.jl/dev/model_search/
└ @ MLJBase ~/.julia/packages/MLJBase/t7MaX/src/tasks.jl:103
┌ Info:
│ is_probabilistic = true
│ input_scitype = ScientificTypes.Table{Union{AbstractArray{Count,1}, AbstractArray{Unknown,1}}}
└ target_scitype = AbstractArray{Count,1}
┌ Warning: Trying to coerce from `Union{Missing, Float64}` to `Count`.
│ Coerced to `Union{Missing,Count}` instead.
└ @ ScientificTypes ~/.julia/packages/ScientificTypes/Oy5C1/src/conventions/mlj/utils.jl:39
┌ Warning: SupervisedTask is deprecated. For model search options, see https://alan-turing-institute.github.io/MLJ.jl/dev/model_search/
└ @ MLJBase ~/.julia/packages/MLJBase/t7MaX/src/tasks.jl:103
┌ Info:
│ is_probabilistic = false
│ input_scitype = ScientificTypes.Table{Union{AbstractArray{Continuous,1}, AbstractArray{Multiclass{4},1}, AbstractArray{Union{Missing, Count},1}}}
└ target_scitype = AbstractArray{Count,1}
┌ Warning: SupervisedTask is deprecated. For model search options, see https://alan-turing-institute.github.io/MLJ.jl/dev/model_search/
└ @ MLJBase ~/.julia/packages/MLJBase/t7MaX/src/tasks.jl:103
┌ Info:
│ is_probabilistic = true
│ input_scitype = ScientificTypes.Table{Union{AbstractArray{Continuous,1}, AbstractArray{Multiclass{4},1}, AbstractArray{Union{Missing, Count},1}}}
└ target_scitype = AbstractArray{Count,1}
Test Summary: | Pass Total
tasks | 19 19
Test Summary: | Pass Total
scitypes | 3 3
Testing MLJ tests passed