Package evaluation of SDeMo on Julia 1.13.0-DEV.897 (a39797a4fb*) started at 2025-07-24T16:59:39.838


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

Installing PkgEval dependencies (TestEnv)...

Set-up completed after 10.08s


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

Installing SDeMo...
   Resolving package versions...
    Updating `~/.julia/environments/v1.13/Project.toml`
  [3e5feb82] + SDeMo v1.5.0
    Updating `~/.julia/environments/v1.13/Manifest.toml`
  [66dad0bd] + AliasTables v1.1.3
  [7d9fca2a] + Arpack v0.5.4
  [34da2185] + Compat v4.17.0
  [9a962f9c] + DataAPI v1.16.0
  [864edb3b] + DataStructures v0.18.22
  [31c24e10] + Distributions v0.25.120
  [ffbed154] + DocStringExtensions v0.9.5
  [1a297f60] + FillArrays v1.13.0
  [34004b35] + HypergeometricFunctions v0.3.28
  [92d709cd] + IrrationalConstants v0.2.4
  [692b3bcd] + JLLWrappers v1.7.1
  [682c06a0] + JSON v0.21.4
  [2ab3a3ac] + LogExpFunctions v0.3.29
  [e1d29d7a] + Missings v1.2.0
  [6f286f6a] + MultivariateStats v0.10.3
  [bac558e1] + OrderedCollections v1.8.1
  [90014a1f] + PDMats v0.11.35
  [69de0a69] + Parsers v2.8.3
  [aea7be01] + PrecompileTools v1.3.2
  [21216c6a] + Preferences v1.4.3
  [43287f4e] + PtrArrays v1.3.0
  [1fd47b50] + QuadGK v2.11.2
  [189a3867] + Reexport v1.2.2
  [79098fc4] + Rmath v0.8.0
  [3e5feb82] + SDeMo v1.5.0
  [a2af1166] + SortingAlgorithms v1.2.1
  [276daf66] + SpecialFunctions v2.5.1
  [10745b16] + Statistics v1.11.1
  [82ae8749] + StatsAPI v1.7.1
  [2913bbd2] + StatsBase v0.34.5
  [4c63d2b9] + StatsFuns v1.5.0
  [1c621080] + TestItems v1.0.0
⌅ [68821587] + Arpack_jll v3.5.1+1
  [efe28fd5] + OpenSpecFun_jll v0.5.6+0
  [f50d1b31] + Rmath_jll v0.5.1+0
  [0dad84c5] + ArgTools v1.1.2
  [56f22d72] + Artifacts v1.11.0
  [2a0f44e3] + Base64 v1.11.0
  [ade2ca70] + Dates v1.11.0
  [f43a241f] + Downloads v1.7.0
  [7b1f6079] + FileWatching v1.11.0
  [b77e0a4c] + InteractiveUtils v1.11.0
  [ac6e5ff7] + JuliaSyntaxHighlighting v1.12.0
  [b27032c2] + LibCURL v0.6.4
  [76f85450] + LibGit2 v1.11.0
  [8f399da3] + Libdl v1.11.0
  [37e2e46d] + LinearAlgebra v1.13.0
  [56ddb016] + Logging v1.11.0
  [d6f4376e] + Markdown v1.11.0
  [a63ad114] + Mmap v1.11.0
  [ca575930] + NetworkOptions v1.3.0
  [44cfe95a] + Pkg v1.13.0
  [de0858da] + Printf v1.11.0
  [9a3f8284] + Random v1.11.0
  [ea8e919c] + SHA v0.7.0
  [9e88b42a] + Serialization v1.11.0
  [2f01184e] + SparseArrays v1.13.0
  [f489334b] + StyledStrings v1.11.0
  [4607b0f0] + SuiteSparse
  [fa267f1f] + TOML v1.0.3
  [a4e569a6] + Tar v1.10.0
  [cf7118a7] + UUIDs v1.11.0
  [4ec0a83e] + Unicode v1.11.0
  [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1
  [deac9b47] + LibCURL_jll v8.14.1+1
  [e37daf67] + LibGit2_jll v1.9.1+0
  [29816b5a] + LibSSH2_jll v1.11.3+1
  [14a3606d] + MozillaCACerts_jll v2025.7.15
  [4536629a] + OpenBLAS_jll v0.3.29+0
  [05823500] + OpenLibm_jll v0.8.5+0
  [458c3c95] + OpenSSL_jll v3.5.1+0
  [efcefdf7] + PCRE2_jll v10.45.0+0
  [bea87d4a] + SuiteSparse_jll v7.10.1+0
  [83775a58] + Zlib_jll v1.3.1+2
  [8e850b90] + libblastrampoline_jll v5.13.1+0
  [8e850ede] + nghttp2_jll v1.65.0+0
  [3f19e933] + p7zip_jll v17.5.0+2
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m`

Installation completed after 4.52s


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# Precompilation
#

Precompiling PkgEval dependencies...

Precompiling package dependencies...

Precompilation completed after 33.09s


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

     Testing SDeMo
      Status `/tmp/jl_HgOFlb/Project.toml`
  [3e5feb82] SDeMo v1.5.0
  [10745b16] Statistics v1.11.1
  [f8b46487] TestItemRunner v1.1.0
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_HgOFlb/Manifest.toml`
  [66dad0bd] AliasTables v1.1.3
  [7d9fca2a] Arpack v0.5.4
  [34da2185] Compat v4.17.0
  [9a962f9c] DataAPI v1.16.0
  [864edb3b] DataStructures v0.18.22
  [31c24e10] Distributions v0.25.120
  [ffbed154] DocStringExtensions v0.9.5
  [1a297f60] FillArrays v1.13.0
  [34004b35] HypergeometricFunctions v0.3.28
  [92d709cd] IrrationalConstants v0.2.4
  [692b3bcd] JLLWrappers v1.7.1
  [682c06a0] JSON v0.21.4
  [2ab3a3ac] LogExpFunctions v0.3.29
  [e1d29d7a] Missings v1.2.0
  [6f286f6a] MultivariateStats v0.10.3
  [bac558e1] OrderedCollections v1.8.1
  [90014a1f] PDMats v0.11.35
  [69de0a69] Parsers v2.8.3
  [aea7be01] PrecompileTools v1.3.2
  [21216c6a] Preferences v1.4.3
  [43287f4e] PtrArrays v1.3.0
  [1fd47b50] QuadGK v2.11.2
  [189a3867] Reexport v1.2.2
  [79098fc4] Rmath v0.8.0
  [3e5feb82] SDeMo v1.5.0
  [a2af1166] SortingAlgorithms v1.2.1
  [276daf66] SpecialFunctions v2.5.1
  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.7.1
  [2913bbd2] StatsBase v0.34.5
  [4c63d2b9] StatsFuns v1.5.0
  [f8b46487] TestItemRunner v1.1.0
  [1c621080] TestItems v1.0.0
⌅ [68821587] Arpack_jll v3.5.1+1
  [efe28fd5] OpenSpecFun_jll v0.5.6+0
  [f50d1b31] Rmath_jll v0.5.1+0
  [0dad84c5] ArgTools v1.1.2
  [56f22d72] Artifacts v1.11.0
  [2a0f44e3] Base64 v1.11.0
  [ade2ca70] Dates v1.11.0
  [f43a241f] Downloads v1.7.0
  [7b1f6079] FileWatching v1.11.0
  [b77e0a4c] InteractiveUtils v1.11.0
  [ac6e5ff7] JuliaSyntaxHighlighting v1.12.0
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.13.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [a63ad114] Mmap v1.11.0
  [ca575930] NetworkOptions v1.3.0
  [44cfe95a] Pkg v1.13.0
  [de0858da] Printf v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization v1.11.0
  [2f01184e] SparseArrays v1.13.0
  [f489334b] StyledStrings v1.11.0
  [4607b0f0] SuiteSparse
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [8dfed614] Test v1.11.0
  [cf7118a7] UUIDs v1.11.0
  [4ec0a83e] Unicode v1.11.0
  [e66e0078] CompilerSupportLibraries_jll v1.3.0+1
  [deac9b47] LibCURL_jll v8.14.1+1
  [e37daf67] LibGit2_jll v1.9.1+0
  [29816b5a] LibSSH2_jll v1.11.3+1
  [14a3606d] MozillaCACerts_jll v2025.7.15
  [4536629a] OpenBLAS_jll v0.3.29+0
  [05823500] OpenLibm_jll v0.8.5+0
  [458c3c95] OpenSSL_jll v3.5.1+0
  [efcefdf7] PCRE2_jll v10.45.0+0
  [bea87d4a] SuiteSparse_jll v7.10.1+0
  [83775a58] Zlib_jll v1.3.1+2
  [8e850b90] libblastrampoline_jll v5.13.1+0
  [8e850ede] nghttp2_jll v1.65.0+0
  [3f19e933] p7zip_jll v17.5.0+2
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading.
     Testing Running tests...
Precompiling packages...
   4492.2 ms  ✓ Distributions → DistributionsTestExt
  1 dependency successfully precompiled in 6 seconds. 49 already precompiled.
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
[ Info: Baseline mcc: -2.8367742685852565e-17
[ Info: Optimal 1 variables model - mcc ≈ 0.7272
[ Info: Optimal 2 variables model - mcc ≈ 0.7394
[ Info: Optimal 3 variables model - mcc ≈ 0.7498
[ Info: Optimal 4 variables model - mcc ≈ 0.7789
[ Info: Optimal 5 variables model - mcc ≈ 0.802
[ Info: Returning model with 5 variables - mcc ≈ 0.802
[ Info: [  0%] LOSS: training ≈ 0.4988 validation ≈ 0.4771 ( 96%)
[ Info: [  1%] LOSS: training ≈ 0.4277 validation ≈ 0.4029 ( 94%)
[ Info: [  2%] LOSS: training ≈ 0.3932 validation ≈ 0.364  ( 93%)
[ Info: [  2%] LOSS: training ≈ 0.373  validation ≈ 0.3396 ( 91%)
[ Info: [  2%] LOSS: training ≈ 0.3596 validation ≈ 0.3227 ( 90%)
[ Info: [  3%] LOSS: training ≈ 0.3499 validation ≈ 0.3102 ( 89%)
[ Info: [  4%] LOSS: training ≈ 0.3426 validation ≈ 0.3003 ( 88%)
[ Info: [  4%] LOSS: training ≈ 0.3368 validation ≈ 0.2924 ( 87%)
[ Info: [  4%] LOSS: training ≈ 0.332  validation ≈ 0.2858 ( 86%)
[ Info: [  5%] LOSS: training ≈ 0.3279 validation ≈ 0.2802 ( 85%)
[ Info: [  6%] LOSS: training ≈ 0.3244 validation ≈ 0.2753 ( 85%)
[ Info: [  6%] LOSS: training ≈ 0.3213 validation ≈ 0.2711 ( 84%)
[ Info: [  6%] LOSS: training ≈ 0.3186 validation ≈ 0.2674 ( 84%)
[ Info: [  7%] LOSS: training ≈ 0.3162 validation ≈ 0.264  ( 84%)
[ Info: [  8%] LOSS: training ≈ 0.3139 validation ≈ 0.261  ( 83%)
[ Info: [  8%] LOSS: training ≈ 0.3119 validation ≈ 0.2583 ( 83%)
[ Info: [  8%] LOSS: training ≈ 0.31   validation ≈ 0.2559 ( 83%)
[ Info: [  9%] LOSS: training ≈ 0.3082 validation ≈ 0.2536 ( 82%)
[ Info: [ 10%] LOSS: training ≈ 0.3066 validation ≈ 0.2516 ( 82%)
[ Info: [ 10%] LOSS: training ≈ 0.305  validation ≈ 0.2497 ( 82%)
[ Info: [ 10%] LOSS: training ≈ 0.3036 validation ≈ 0.2479 ( 82%)
[ Info: [ 11%] LOSS: training ≈ 0.3022 validation ≈ 0.2463 ( 81%)
[ Info: [ 12%] LOSS: training ≈ 0.301  validation ≈ 0.2448 ( 81%)
[ Info: [ 12%] LOSS: training ≈ 0.2997 validation ≈ 0.2433 ( 81%)
[ Info: [ 12%] LOSS: training ≈ 0.2986 validation ≈ 0.242  ( 81%)
[ Info: [ 13%] LOSS: training ≈ 0.2975 validation ≈ 0.2408 ( 81%)
[ Info: [ 14%] LOSS: training ≈ 0.2964 validation ≈ 0.2396 ( 81%)
[ Info: [ 14%] LOSS: training ≈ 0.2954 validation ≈ 0.2385 ( 81%)
[ Info: [ 14%] LOSS: training ≈ 0.2945 validation ≈ 0.2375 ( 81%)
[ Info: [ 15%] LOSS: training ≈ 0.2936 validation ≈ 0.2366 ( 81%)
[ Info: [ 16%] LOSS: training ≈ 0.2927 validation ≈ 0.2356 ( 81%)
[ Info: [ 16%] LOSS: training ≈ 0.2918 validation ≈ 0.2348 ( 80%)
[ Info: [ 16%] LOSS: training ≈ 0.291  validation ≈ 0.234  ( 80%)
[ Info: [ 17%] LOSS: training ≈ 0.2903 validation ≈ 0.2332 ( 80%)
[ Info: [ 18%] LOSS: training ≈ 0.2895 validation ≈ 0.2325 ( 80%)
[ Info: [ 18%] LOSS: training ≈ 0.2888 validation ≈ 0.2318 ( 80%)
[ Info: [ 18%] LOSS: training ≈ 0.2881 validation ≈ 0.2311 ( 80%)
[ Info: [ 19%] LOSS: training ≈ 0.2874 validation ≈ 0.2305 ( 80%)
[ Info: [ 20%] LOSS: training ≈ 0.2868 validation ≈ 0.2299 ( 80%)
[ Info: [ 20%] LOSS: training ≈ 0.2862 validation ≈ 0.2293 ( 80%)
[ Info: [ 20%] LOSS: training ≈ 0.2856 validation ≈ 0.2287 ( 80%)
[ Info: [ 21%] LOSS: training ≈ 0.285  validation ≈ 0.2282 ( 80%)
[ Info: [ 22%] LOSS: training ≈ 0.2845 validation ≈ 0.2277 ( 80%)
[ Info: [ 22%] LOSS: training ≈ 0.2839 validation ≈ 0.2272 ( 80%)
[ Info: [ 22%] LOSS: training ≈ 0.2834 validation ≈ 0.2268 ( 80%)
[ Info: [ 23%] LOSS: training ≈ 0.2829 validation ≈ 0.2263 ( 80%)
[ Info: [ 24%] LOSS: training ≈ 0.2824 validation ≈ 0.2259 ( 80%)
[ Info: [ 24%] LOSS: training ≈ 0.2819 validation ≈ 0.2255 ( 80%)
[ Info: [ 24%] LOSS: training ≈ 0.2815 validation ≈ 0.2251 ( 80%)
[ Info: [ 25%] LOSS: training ≈ 0.2811 validation ≈ 0.2247 ( 80%)
[ Info: [ 26%] LOSS: training ≈ 0.2806 validation ≈ 0.2243 ( 80%)
[ Info: [ 26%] LOSS: training ≈ 0.2802 validation ≈ 0.224  ( 80%)
[ Info: [ 26%] LOSS: training ≈ 0.2798 validation ≈ 0.2237 ( 80%)
[ Info: [ 27%] LOSS: training ≈ 0.2794 validation ≈ 0.2233 ( 80%)
[ Info: [ 28%] LOSS: training ≈ 0.2791 validation ≈ 0.223  ( 80%)
[ Info: [ 28%] LOSS: training ≈ 0.2787 validation ≈ 0.2227 ( 80%)
[ Info: [ 28%] LOSS: training ≈ 0.2784 validation ≈ 0.2224 ( 80%)
[ Info: [ 29%] LOSS: training ≈ 0.278  validation ≈ 0.2221 ( 80%)
[ Info: [ 30%] LOSS: training ≈ 0.2777 validation ≈ 0.2219 ( 80%)
[ Info: [ 30%] LOSS: training ≈ 0.2774 validation ≈ 0.2216 ( 80%)
[ Info: [ 30%] LOSS: training ≈ 0.2771 validation ≈ 0.2213 ( 80%)
[ Info: [ 31%] LOSS: training ≈ 0.2767 validation ≈ 0.2211 ( 80%)
[ Info: [ 32%] LOSS: training ≈ 0.2765 validation ≈ 0.2209 ( 80%)
[ Info: [ 32%] LOSS: training ≈ 0.2762 validation ≈ 0.2206 ( 80%)
[ Info: [ 32%] LOSS: training ≈ 0.2759 validation ≈ 0.2204 ( 80%)
[ Info: [ 33%] LOSS: training ≈ 0.2756 validation ≈ 0.2202 ( 80%)
[ Info: [ 34%] LOSS: training ≈ 0.2754 validation ≈ 0.22   ( 80%)
[ Info: [ 34%] LOSS: training ≈ 0.2751 validation ≈ 0.2198 ( 80%)
[ Info: [ 34%] LOSS: training ≈ 0.2749 validation ≈ 0.2196 ( 80%)
[ Info: [ 35%] LOSS: training ≈ 0.2746 validation ≈ 0.2194 ( 80%)
[ Info: [ 36%] LOSS: training ≈ 0.2744 validation ≈ 0.2192 ( 80%)
[ Info: [ 36%] LOSS: training ≈ 0.2742 validation ≈ 0.219  ( 80%)
[ Info: [ 36%] LOSS: training ≈ 0.274  validation ≈ 0.2188 ( 80%)
[ Info: [ 37%] LOSS: training ≈ 0.2737 validation ≈ 0.2186 ( 80%)
[ Info: [ 38%] LOSS: training ≈ 0.2735 validation ≈ 0.2185 ( 80%)
[ Info: [ 38%] LOSS: training ≈ 0.2733 validation ≈ 0.2183 ( 80%)
[ Info: [ 38%] LOSS: training ≈ 0.2731 validation ≈ 0.2181 ( 80%)
[ Info: [ 39%] LOSS: training ≈ 0.2729 validation ≈ 0.218  ( 80%)
[ Info: [ 40%] LOSS: training ≈ 0.2727 validation ≈ 0.2178 ( 80%)
[ Info: [ 40%] LOSS: training ≈ 0.2726 validation ≈ 0.2177 ( 80%)
[ Info: [ 40%] LOSS: training ≈ 0.2724 validation ≈ 0.2175 ( 80%)
[ Info: [ 41%] LOSS: training ≈ 0.2722 validation ≈ 0.2174 ( 80%)
[ Info: [ 42%] LOSS: training ≈ 0.272  validation ≈ 0.2173 ( 80%)
[ Info: [ 42%] LOSS: training ≈ 0.2719 validation ≈ 0.2171 ( 80%)
[ Info: [ 42%] LOSS: training ≈ 0.2717 validation ≈ 0.217  ( 80%)
[ Info: [ 43%] LOSS: training ≈ 0.2716 validation ≈ 0.2169 ( 80%)
[ Info: [ 44%] LOSS: training ≈ 0.2714 validation ≈ 0.2167 ( 80%)
[ Info: [ 44%] LOSS: training ≈ 0.2713 validation ≈ 0.2166 ( 80%)
[ Info: [ 44%] LOSS: training ≈ 0.2711 validation ≈ 0.2165 ( 80%)
[ Info: [ 45%] LOSS: training ≈ 0.271  validation ≈ 0.2164 ( 80%)
[ Info: [ 46%] LOSS: training ≈ 0.2708 validation ≈ 0.2163 ( 80%)
[ Info: [ 46%] LOSS: training ≈ 0.2707 validation ≈ 0.2162 ( 80%)
[ Info: [ 46%] LOSS: training ≈ 0.2706 validation ≈ 0.2161 ( 80%)
[ Info: [ 47%] LOSS: training ≈ 0.2705 validation ≈ 0.216  ( 80%)
[ Info: [ 48%] LOSS: training ≈ 0.2703 validation ≈ 0.2159 ( 80%)
[ Info: [ 48%] LOSS: training ≈ 0.2702 validation ≈ 0.2158 ( 80%)
[ Info: [ 48%] LOSS: training ≈ 0.2701 validation ≈ 0.2157 ( 80%)
[ Info: [ 49%] LOSS: training ≈ 0.27   validation ≈ 0.2156 ( 80%)
[ Info: [ 50%] LOSS: training ≈ 0.2699 validation ≈ 0.2155 ( 80%)
[ Info: [ 50%] LOSS: training ≈ 0.2698 validation ≈ 0.2154 ( 80%)
[ Info: [ 50%] LOSS: training ≈ 0.2696 validation ≈ 0.2153 ( 80%)
[ Info: [ 51%] LOSS: training ≈ 0.2695 validation ≈ 0.2152 ( 80%)
[ Info: [ 52%] LOSS: training ≈ 0.2694 validation ≈ 0.2151 ( 80%)
[ Info: [ 52%] LOSS: training ≈ 0.2693 validation ≈ 0.215  ( 80%)
[ Info: [ 52%] LOSS: training ≈ 0.2692 validation ≈ 0.2149 ( 80%)
[ Info: [ 53%] LOSS: training ≈ 0.2691 validation ≈ 0.2149 ( 80%)
[ Info: [ 54%] LOSS: training ≈ 0.269  validation ≈ 0.2148 ( 80%)
[ Info: [ 54%] LOSS: training ≈ 0.269  validation ≈ 0.2147 ( 80%)
[ Info: [ 55%] LOSS: training ≈ 0.2689 validation ≈ 0.2146 ( 80%)
[ Info: [ 55%] LOSS: training ≈ 0.2688 validation ≈ 0.2145 ( 80%)
[ Info: [ 56%] LOSS: training ≈ 0.2687 validation ≈ 0.2145 ( 80%)
[ Info: [ 56%] LOSS: training ≈ 0.2686 validation ≈ 0.2144 ( 80%)
[ Info: [ 56%] LOSS: training ≈ 0.2685 validation ≈ 0.2143 ( 80%)
[ Info: [ 57%] LOSS: training ≈ 0.2684 validation ≈ 0.2143 ( 80%)
[ Info: [ 57%] LOSS: training ≈ 0.2684 validation ≈ 0.2142 ( 80%)
[ Info: [ 58%] LOSS: training ≈ 0.2683 validation ≈ 0.2141 ( 80%)
[ Info: [ 58%] LOSS: training ≈ 0.2682 validation ≈ 0.2141 ( 80%)
[ Info: [ 59%] LOSS: training ≈ 0.2681 validation ≈ 0.214  ( 80%)
[ Info: [ 60%] LOSS: training ≈ 0.2681 validation ≈ 0.2139 ( 80%)
[ Info: [ 60%] LOSS: training ≈ 0.268  validation ≈ 0.2139 ( 80%)
[ Info: [ 60%] LOSS: training ≈ 0.2679 validation ≈ 0.2138 ( 80%)
[ Info: [ 61%] LOSS: training ≈ 0.2679 validation ≈ 0.2138 ( 80%)
[ Info: [ 62%] LOSS: training ≈ 0.2678 validation ≈ 0.2137 ( 80%)
[ Info: [ 62%] LOSS: training ≈ 0.2677 validation ≈ 0.2136 ( 80%)
[ Info: [ 62%] LOSS: training ≈ 0.2677 validation ≈ 0.2136 ( 80%)
[ Info: [ 63%] LOSS: training ≈ 0.2676 validation ≈ 0.2135 ( 80%)
[ Info: [ 64%] LOSS: training ≈ 0.2675 validation ≈ 0.2135 ( 80%)
[ Info: [ 64%] LOSS: training ≈ 0.2675 validation ≈ 0.2134 ( 80%)
[ Info: [ 64%] LOSS: training ≈ 0.2674 validation ≈ 0.2134 ( 80%)
[ Info: [ 65%] LOSS: training ≈ 0.2674 validation ≈ 0.2133 ( 80%)
[ Info: [ 66%] LOSS: training ≈ 0.2673 validation ≈ 0.2133 ( 80%)
[ Info: [ 66%] LOSS: training ≈ 0.2673 validation ≈ 0.2132 ( 80%)
[ Info: [ 66%] LOSS: training ≈ 0.2672 validation ≈ 0.2132 ( 80%)
[ Info: [ 67%] LOSS: training ≈ 0.2671 validation ≈ 0.2131 ( 80%)
[ Info: [ 68%] LOSS: training ≈ 0.2671 validation ≈ 0.2131 ( 80%)
[ Info: [ 68%] LOSS: training ≈ 0.267  validation ≈ 0.213  ( 80%)
[ Info: [ 68%] LOSS: training ≈ 0.267  validation ≈ 0.213  ( 80%)
[ Info: [ 69%] LOSS: training ≈ 0.2669 validation ≈ 0.2129 ( 80%)
[ Info: [ 70%] LOSS: training ≈ 0.2669 validation ≈ 0.2129 ( 80%)
[ Info: [ 70%] LOSS: training ≈ 0.2669 validation ≈ 0.2129 ( 80%)
[ Info: [ 70%] LOSS: training ≈ 0.2668 validation ≈ 0.2128 ( 80%)
[ Info: [ 71%] LOSS: training ≈ 0.2668 validation ≈ 0.2128 ( 80%)
[ Info: [ 72%] LOSS: training ≈ 0.2667 validation ≈ 0.2127 ( 80%)
[ Info: [ 72%] LOSS: training ≈ 0.2667 validation ≈ 0.2127 ( 80%)
[ Info: [ 72%] LOSS: training ≈ 0.2666 validation ≈ 0.2127 ( 80%)
[ Info: [ 73%] LOSS: training ≈ 0.2666 validation ≈ 0.2126 ( 80%)
[ Info: [ 74%] LOSS: training ≈ 0.2665 validation ≈ 0.2126 ( 80%)
[ Info: [ 74%] LOSS: training ≈ 0.2665 validation ≈ 0.2125 ( 80%)
[ Info: [ 74%] LOSS: training ≈ 0.2665 validation ≈ 0.2125 ( 80%)
[ Info: [ 75%] LOSS: training ≈ 0.2664 validation ≈ 0.2125 ( 80%)
[ Info: [ 76%] LOSS: training ≈ 0.2664 validation ≈ 0.2124 ( 80%)
[ Info: [ 76%] LOSS: training ≈ 0.2663 validation ≈ 0.2124 ( 80%)
[ Info: [ 76%] LOSS: training ≈ 0.2663 validation ≈ 0.2124 ( 80%)
[ Info: [ 77%] LOSS: training ≈ 0.2663 validation ≈ 0.2123 ( 80%)
[ Info: [ 78%] LOSS: training ≈ 0.2662 validation ≈ 0.2123 ( 80%)
[ Info: [ 78%] LOSS: training ≈ 0.2662 validation ≈ 0.2123 ( 80%)
[ Info: [ 78%] LOSS: training ≈ 0.2662 validation ≈ 0.2122 ( 80%)
[ Info: [ 79%] LOSS: training ≈ 0.2661 validation ≈ 0.2122 ( 80%)
[ Info: [ 80%] LOSS: training ≈ 0.2661 validation ≈ 0.2122 ( 80%)
[ Info: [ 80%] LOSS: training ≈ 0.2661 validation ≈ 0.2121 ( 80%)
[ Info: [ 80%] LOSS: training ≈ 0.266  validation ≈ 0.2121 ( 80%)
[ Info: [ 81%] LOSS: training ≈ 0.266  validation ≈ 0.2121 ( 80%)
[ Info: [ 82%] LOSS: training ≈ 0.266  validation ≈ 0.2121 ( 80%)
[ Info: [ 82%] LOSS: training ≈ 0.2659 validation ≈ 0.212  ( 80%)
[ Info: [ 82%] LOSS: training ≈ 0.2659 validation ≈ 0.212  ( 80%)
[ Info: [ 83%] LOSS: training ≈ 0.2659 validation ≈ 0.212  ( 80%)
[ Info: [ 84%] LOSS: training ≈ 0.2659 validation ≈ 0.2119 ( 80%)
[ Info: [ 84%] LOSS: training ≈ 0.2658 validation ≈ 0.2119 ( 80%)
[ Info: [ 84%] LOSS: training ≈ 0.2658 validation ≈ 0.2119 ( 80%)
[ Info: [ 85%] LOSS: training ≈ 0.2658 validation ≈ 0.2119 ( 80%)
[ Info: [ 86%] LOSS: training ≈ 0.2657 validation ≈ 0.2118 ( 80%)
[ Info: [ 86%] LOSS: training ≈ 0.2657 validation ≈ 0.2118 ( 80%)
[ Info: [ 86%] LOSS: training ≈ 0.2657 validation ≈ 0.2118 ( 80%)
[ Info: [ 87%] LOSS: training ≈ 0.2657 validation ≈ 0.2118 ( 80%)
[ Info: [ 88%] LOSS: training ≈ 0.2656 validation ≈ 0.2117 ( 80%)
[ Info: [ 88%] LOSS: training ≈ 0.2656 validation ≈ 0.2117 ( 80%)
[ Info: [ 88%] LOSS: training ≈ 0.2656 validation ≈ 0.2117 ( 80%)
[ Info: [ 89%] LOSS: training ≈ 0.2656 validation ≈ 0.2117 ( 80%)
[ Info: [ 90%] LOSS: training ≈ 0.2655 validation ≈ 0.2117 ( 80%)
[ Info: [ 90%] LOSS: training ≈ 0.2655 validation ≈ 0.2116 ( 80%)
[ Info: [ 90%] LOSS: training ≈ 0.2655 validation ≈ 0.2116 ( 80%)
[ Info: [ 91%] LOSS: training ≈ 0.2655 validation ≈ 0.2116 ( 80%)
[ Info: [ 92%] LOSS: training ≈ 0.2655 validation ≈ 0.2116 ( 80%)
[ Info: [ 92%] LOSS: training ≈ 0.2654 validation ≈ 0.2115 ( 80%)
[ Info: [ 92%] LOSS: training ≈ 0.2654 validation ≈ 0.2115 ( 80%)
[ Info: [ 93%] LOSS: training ≈ 0.2654 validation ≈ 0.2115 ( 80%)
[ Info: [ 94%] LOSS: training ≈ 0.2654 validation ≈ 0.2115 ( 80%)
[ Info: [ 94%] LOSS: training ≈ 0.2653 validation ≈ 0.2115 ( 80%)
[ Info: [ 94%] LOSS: training ≈ 0.2653 validation ≈ 0.2114 ( 80%)
[ Info: [ 95%] LOSS: training ≈ 0.2653 validation ≈ 0.2114 ( 80%)
[ Info: [ 96%] LOSS: training ≈ 0.2653 validation ≈ 0.2114 ( 80%)
[ Info: [ 96%] LOSS: training ≈ 0.2653 validation ≈ 0.2114 ( 80%)
[ Info: [ 96%] LOSS: training ≈ 0.2652 validation ≈ 0.2114 ( 80%)
[ Info: [ 97%] LOSS: training ≈ 0.2652 validation ≈ 0.2114 ( 80%)
[ Info: [ 98%] LOSS: training ≈ 0.2652 validation ≈ 0.2113 ( 80%)
[ Info: [ 98%] LOSS: training ≈ 0.2652 validation ≈ 0.2113 ( 80%)
[ Info: [ 98%] LOSS: training ≈ 0.2652 validation ≈ 0.2113 ( 80%)
[ Info: [ 99%] LOSS: training ≈ 0.2652 validation ≈ 0.2113 ( 80%)
[ Info: [100%] LOSS: training ≈ 0.2651 validation ≈ 0.2113 ( 80%)
[ Info: [100%] LOSS: training ≈ 0.2651 validation ≈ 0.2113 ( 80%)
[ Info: [  0%] LOSS: training ≈ 0.4215
[ Info: [  1%] LOSS: training ≈ 0.3806
[ Info: [  2%] LOSS: training ≈ 0.3564
[ Info: [  2%] LOSS: training ≈ 0.3399
[ Info: [  2%] LOSS: training ≈ 0.3279
[ Info: [  3%] LOSS: training ≈ 0.3185
[ Info: [  4%] LOSS: training ≈ 0.311 
[ Info: [  4%] LOSS: training ≈ 0.3048
[ Info: [  4%] LOSS: training ≈ 0.2996
[ Info: [  5%] LOSS: training ≈ 0.2952
[ Info: [  6%] LOSS: training ≈ 0.2914
[ Info: [  6%] LOSS: training ≈ 0.2881
[ Info: [  6%] LOSS: training ≈ 0.2852
[ Info: [  7%] LOSS: training ≈ 0.2826
[ Info: [  8%] LOSS: training ≈ 0.2802
[ Info: [  8%] LOSS: training ≈ 0.2782
[ Info: [  8%] LOSS: training ≈ 0.2763
[ Info: [  9%] LOSS: training ≈ 0.2746
[ Info: [ 10%] LOSS: training ≈ 0.2731
[ Info: [ 10%] LOSS: training ≈ 0.2717
[ Info: [ 10%] LOSS: training ≈ 0.2704
[ Info: [ 11%] LOSS: training ≈ 0.2692
[ Info: [ 12%] LOSS: training ≈ 0.2681
[ Info: [ 12%] LOSS: training ≈ 0.2671
[ Info: [ 12%] LOSS: training ≈ 0.2662
[ Info: [ 13%] LOSS: training ≈ 0.2654
[ Info: [ 14%] LOSS: training ≈ 0.2646
[ Info: [ 14%] LOSS: training ≈ 0.2639
[ Info: [ 14%] LOSS: training ≈ 0.2632
[ Info: [ 15%] LOSS: training ≈ 0.2626
[ Info: [ 16%] LOSS: training ≈ 0.262 
[ Info: [ 16%] LOSS: training ≈ 0.2614
[ Info: [ 16%] LOSS: training ≈ 0.2609
[ Info: [ 17%] LOSS: training ≈ 0.2605
[ Info: [ 18%] LOSS: training ≈ 0.26  
[ Info: [ 18%] LOSS: training ≈ 0.2596
[ Info: [ 18%] LOSS: training ≈ 0.2592
[ Info: [ 19%] LOSS: training ≈ 0.2589
[ Info: [ 20%] LOSS: training ≈ 0.2585
[ Info: [ 20%] LOSS: training ≈ 0.2582
[ Info: [ 20%] LOSS: training ≈ 0.2579
[ Info: [ 21%] LOSS: training ≈ 0.2576
[ Info: [ 22%] LOSS: training ≈ 0.2573
[ Info: [ 22%] LOSS: training ≈ 0.2571
[ Info: [ 22%] LOSS: training ≈ 0.2568
[ Info: [ 23%] LOSS: training ≈ 0.2566
[ Info: [ 24%] LOSS: training ≈ 0.2564
[ Info: [ 24%] LOSS: training ≈ 0.2562
[ Info: [ 24%] LOSS: training ≈ 0.256 
[ Info: [ 25%] LOSS: training ≈ 0.2558
[ Info: [ 26%] LOSS: training ≈ 0.2557
[ Info: [ 26%] LOSS: training ≈ 0.2555
[ Info: [ 26%] LOSS: training ≈ 0.2554
[ Info: [ 27%] LOSS: training ≈ 0.2552
[ Info: [ 28%] LOSS: training ≈ 0.2551
[ Info: [ 28%] LOSS: training ≈ 0.255 
[ Info: [ 28%] LOSS: training ≈ 0.2548
[ Info: [ 29%] LOSS: training ≈ 0.2547
[ Info: [ 30%] LOSS: training ≈ 0.2546
[ Info: [ 30%] LOSS: training ≈ 0.2545
[ Info: [ 30%] LOSS: training ≈ 0.2544
[ Info: [ 31%] LOSS: training ≈ 0.2543
[ Info: [ 32%] LOSS: training ≈ 0.2542
[ Info: [ 32%] LOSS: training ≈ 0.2541
[ Info: [ 32%] LOSS: training ≈ 0.2541
[ Info: [ 33%] LOSS: training ≈ 0.254 
[ Info: [ 34%] LOSS: training ≈ 0.2539
[ Info: [ 34%] LOSS: training ≈ 0.2538
[ Info: [ 34%] LOSS: training ≈ 0.2538
[ Info: [ 35%] LOSS: training ≈ 0.2537
[ Info: [ 36%] LOSS: training ≈ 0.2536
[ Info: [ 36%] LOSS: training ≈ 0.2536
[ Info: [ 36%] LOSS: training ≈ 0.2535
[ Info: [ 37%] LOSS: training ≈ 0.2535
[ Info: [ 38%] LOSS: training ≈ 0.2534
[ Info: [ 38%] LOSS: training ≈ 0.2534
[ Info: [ 38%] LOSS: training ≈ 0.2533
[ Info: [ 39%] LOSS: training ≈ 0.2533
[ Info: [ 40%] LOSS: training ≈ 0.2532
[ Info: [ 40%] LOSS: training ≈ 0.2532
[ Info: [ 40%] LOSS: training ≈ 0.2532
[ Info: [ 41%] LOSS: training ≈ 0.2531
[ Info: [ 42%] LOSS: training ≈ 0.2531
[ Info: [ 42%] LOSS: training ≈ 0.2531
[ Info: [ 42%] LOSS: training ≈ 0.253 
[ Info: [ 43%] LOSS: training ≈ 0.253 
[ Info: [ 44%] LOSS: training ≈ 0.253 
[ Info: [ 44%] LOSS: training ≈ 0.2529
[ Info: [ 44%] LOSS: training ≈ 0.2529
[ Info: [ 45%] LOSS: training ≈ 0.2529
[ Info: [ 46%] LOSS: training ≈ 0.2529
[ Info: [ 46%] LOSS: training ≈ 0.2528
[ Info: [ 46%] LOSS: training ≈ 0.2528
[ Info: [ 47%] LOSS: training ≈ 0.2528
[ Info: [ 48%] LOSS: training ≈ 0.2528
[ Info: [ 48%] LOSS: training ≈ 0.2527
[ Info: [ 48%] LOSS: training ≈ 0.2527
[ Info: [ 49%] LOSS: training ≈ 0.2527
[ Info: [ 50%] LOSS: training ≈ 0.2527
[ Info: [ 50%] LOSS: training ≈ 0.2527
[ Info: [ 50%] LOSS: training ≈ 0.2527
[ Info: [ 51%] LOSS: training ≈ 0.2526
[ Info: [ 52%] LOSS: training ≈ 0.2526
[ Info: [ 52%] LOSS: training ≈ 0.2526
[ Info: [ 52%] LOSS: training ≈ 0.2526
[ Info: [ 53%] LOSS: training ≈ 0.2526
[ Info: [ 54%] LOSS: training ≈ 0.2526
[ Info: [ 54%] LOSS: training ≈ 0.2525
[ Info: [ 55%] LOSS: training ≈ 0.2525
[ Info: [ 55%] LOSS: training ≈ 0.2525
[ Info: [ 56%] LOSS: training ≈ 0.2525
[ Info: [ 56%] LOSS: training ≈ 0.2525
[ Info: [ 56%] LOSS: training ≈ 0.2525
[ Info: [ 57%] LOSS: training ≈ 0.2525
[ Info: [ 57%] LOSS: training ≈ 0.2525
[ Info: [ 58%] LOSS: training ≈ 0.2525
[ Info: [ 58%] LOSS: training ≈ 0.2525
[ Info: [ 59%] LOSS: training ≈ 0.2524
[ Info: [ 60%] LOSS: training ≈ 0.2524
[ Info: [ 60%] LOSS: training ≈ 0.2524
[ Info: [ 60%] LOSS: training ≈ 0.2524
[ Info: [ 61%] LOSS: training ≈ 0.2524
[ Info: [ 62%] LOSS: training ≈ 0.2524
[ Info: [ 62%] LOSS: training ≈ 0.2524
[ Info: [ 62%] LOSS: training ≈ 0.2524
[ Info: [ 63%] LOSS: training ≈ 0.2524
[ Info: [ 64%] LOSS: training ≈ 0.2524
[ Info: [ 64%] LOSS: training ≈ 0.2524
[ Info: [ 64%] LOSS: training ≈ 0.2524
[ Info: [ 65%] LOSS: training ≈ 0.2524
[ Info: [ 66%] LOSS: training ≈ 0.2523
[ Info: [ 66%] LOSS: training ≈ 0.2523
[ Info: [ 66%] LOSS: training ≈ 0.2523
[ Info: [ 67%] LOSS: training ≈ 0.2523
[ Info: [ 68%] LOSS: training ≈ 0.2523
[ Info: [ 68%] LOSS: training ≈ 0.2523
[ Info: [ 68%] LOSS: training ≈ 0.2523
[ Info: [ 69%] LOSS: training ≈ 0.2523
[ Info: [ 70%] LOSS: training ≈ 0.2523
[ Info: [ 70%] LOSS: training ≈ 0.2523
[ Info: [ 70%] LOSS: training ≈ 0.2523
[ Info: [ 71%] LOSS: training ≈ 0.2523
[ Info: [ 72%] LOSS: training ≈ 0.2523
[ Info: [ 72%] LOSS: training ≈ 0.2523
[ Info: [ 72%] LOSS: training ≈ 0.2523
[ Info: [ 73%] LOSS: training ≈ 0.2523
[ Info: [ 74%] LOSS: training ≈ 0.2523
[ Info: [ 74%] LOSS: training ≈ 0.2523
[ Info: [ 74%] LOSS: training ≈ 0.2523
[ Info: [ 75%] LOSS: training ≈ 0.2523
[ Info: [ 76%] LOSS: training ≈ 0.2523
[ Info: [ 76%] LOSS: training ≈ 0.2523
[ Info: [ 76%] LOSS: training ≈ 0.2523
[ Info: [ 77%] LOSS: training ≈ 0.2523
[ Info: [ 78%] LOSS: training ≈ 0.2523
[ Info: [ 78%] LOSS: training ≈ 0.2523
[ Info: [ 78%] LOSS: training ≈ 0.2522
[ Info: [ 79%] LOSS: training ≈ 0.2522
[ Info: [ 80%] LOSS: training ≈ 0.2522
[ Info: [ 80%] LOSS: training ≈ 0.2522
[ Info: [ 80%] LOSS: training ≈ 0.2522
[ Info: [ 81%] LOSS: training ≈ 0.2522
[ Info: [ 82%] LOSS: training ≈ 0.2522
[ Info: [ 82%] LOSS: training ≈ 0.2522
[ Info: [ 82%] LOSS: training ≈ 0.2522
[ Info: [ 83%] LOSS: training ≈ 0.2522
[ Info: [ 84%] LOSS: training ≈ 0.2522
[ Info: [ 84%] LOSS: training ≈ 0.2522
[ Info: [ 84%] LOSS: training ≈ 0.2522
[ Info: [ 85%] LOSS: training ≈ 0.2522
[ Info: [ 86%] LOSS: training ≈ 0.2522
[ Info: [ 86%] LOSS: training ≈ 0.2522
[ Info: [ 86%] LOSS: training ≈ 0.2522
[ Info: [ 87%] LOSS: training ≈ 0.2522
[ Info: [ 88%] LOSS: training ≈ 0.2522
[ Info: [ 88%] LOSS: training ≈ 0.2522
[ Info: [ 88%] LOSS: training ≈ 0.2522
[ Info: [ 89%] LOSS: training ≈ 0.2522
[ Info: [ 90%] LOSS: training ≈ 0.2522
[ Info: [ 90%] LOSS: training ≈ 0.2522
[ Info: [ 90%] LOSS: training ≈ 0.2522
[ Info: [ 91%] LOSS: training ≈ 0.2522
[ Info: [ 92%] LOSS: training ≈ 0.2522
[ Info: [ 92%] LOSS: training ≈ 0.2522
[ Info: [ 92%] LOSS: training ≈ 0.2522
[ Info: [ 93%] LOSS: training ≈ 0.2522
[ Info: [ 94%] LOSS: training ≈ 0.2522
[ Info: [ 94%] LOSS: training ≈ 0.2522
[ Info: [ 94%] LOSS: training ≈ 0.2522
[ Info: [ 95%] LOSS: training ≈ 0.2522
[ Info: [ 96%] LOSS: training ≈ 0.2522
[ Info: [ 96%] LOSS: training ≈ 0.2522
[ Info: [ 96%] LOSS: training ≈ 0.2522
[ Info: [ 97%] LOSS: training ≈ 0.2522
[ Info: [ 98%] LOSS: training ≈ 0.2522
[ Info: [ 98%] LOSS: training ≈ 0.2522
[ Info: [ 98%] LOSS: training ≈ 0.2522
[ Info: [ 99%] LOSS: training ≈ 0.2522
[ Info: [100%] LOSS: training ≈ 0.2522
[ Info: [100%] LOSS: training ≈ 0.2522
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:90
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:90
[ Info: [ 2 vars.] MCC val. ≈ -0.0
[ Info: [ 3 vars.] MCC val. ≈ 0.417
[ Info: [ 4 vars.] MCC val. ≈ 0.43
[ Info: [ 5 vars.] MCC val. ≈ 0.437
[ Info: [ 6 vars.] MCC val. ≈ 0.444
[ Info: Optimal var. pool: [1, 12, 19, 18, 4, 6]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:44
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:44
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:90
[ Info: [ 0 vars.] MCC val. ≈ -0.0
[ Info: [ 1 vars.] MCC val. ≈ 0.78
[ Info: [ 2 vars.] MCC val. ≈ 0.793
[ Info: [ 3 vars.] MCC val. ≈ 0.815
[ Info: Optimal var. pool: [1, 3, 8]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:44
[ Info: [19 vars.] MCC val. ≈ -0.0
[ Info: [18 vars.] MCC val. ≈ 0.619
[ Info: [17 vars.] MCC val. ≈ 0.779
[ Info: [16 vars.] MCC val. ≈ 0.786
[ Info: Optimal var. pool: [1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:44
[ Info: [ 9 vars.] MCC val. ≈ -0.0
[ Info: [ 8 vars.] MCC val. ≈ 0.801
[ Info: Optimal var. pool: [1, 3, 4, 5, 6, 7, 8, 9]
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:90
[ Info: [ 2 vars.] MCC val. ≈ -0.0
[ Info: [ 3 vars.] MCC val. ≈ 0.523
[ Info: Optimal var. pool: [12, 13, 1]
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:90
[ Info: [ 0 vars.] MCC val. ≈ -0.0
[ Info: [ 1 vars.] MCC val. ≈ 0.752
[ Info: [ 2 vars.] MCC val. ≈ 0.766
[ Info: [ 3 vars.] MCC val. ≈ 0.772
[ Info: [ 4 vars.] MCC val. ≈ 0.773
[ Info: [ 5 vars.] MCC val. ≈ 0.793
[ Info: Optimal var. pool: [8, 15, 5, 14, 4]
Test Summary: | Pass  Total      Time
Package       |  298    298  22m43.2s
     Testing SDeMo tests passed 

Testing completed after 1417.87s

PkgEval succeeded after 1486.95s