Package evaluation of SDeMo on Julia 1.13.0-DEV.912 (a2457e6ed7*) started at 2025-07-27T16:55:02.171


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

Installing PkgEval dependencies (TestEnv)...

Set-up completed after 9.09s


################################################################################
# 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 v8.15.0+0
  [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 4.07s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...

Precompilation completed after 31.43s


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

     Testing SDeMo
      Status `/tmp/jl_fKL4ab/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_fKL4ab/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 v8.15.0+0
  [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...
┌ 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 ≈ 0.7368
[ Info: Optimal 2 variables model - mcc ≈ 0.7662
[ Info: Optimal 3 variables model - mcc ≈ 0.7817
[ Info: Optimal 4 variables model - mcc ≈ 0.7831
[ Info: Returning model with 4 variables - mcc ≈ 0.7831
[ Info: [  0%] LOSS: training ≈ 0.4944 validation ≈ 0.499  (101%)
[ Info: [  1%] LOSS: training ≈ 0.4248 validation ≈ 0.4309 (101%)
[ Info: [  2%] LOSS: training ≈ 0.3903 validation ≈ 0.3949 (101%)
[ Info: [  2%] LOSS: training ≈ 0.3695 validation ≈ 0.3727 (101%)
[ Info: [  2%] LOSS: training ≈ 0.3555 validation ≈ 0.3574 (101%)
[ Info: [  3%] LOSS: training ≈ 0.3453 validation ≈ 0.3462 (100%)
[ Info: [  4%] LOSS: training ≈ 0.3375 validation ≈ 0.3376 (100%)
[ Info: [  4%] LOSS: training ≈ 0.3313 validation ≈ 0.3307 (100%)
[ Info: [  4%] LOSS: training ≈ 0.3263 validation ≈ 0.3249 (100%)
[ Info: [  5%] LOSS: training ≈ 0.322  validation ≈ 0.32   ( 99%)
[ Info: [  6%] LOSS: training ≈ 0.3184 validation ≈ 0.3158 ( 99%)
[ Info: [  6%] LOSS: training ≈ 0.3152 validation ≈ 0.3121 ( 99%)
[ Info: [  6%] LOSS: training ≈ 0.3125 validation ≈ 0.3087 ( 99%)
[ Info: [  7%] LOSS: training ≈ 0.31   validation ≈ 0.3057 ( 99%)
[ Info: [  8%] LOSS: training ≈ 0.3078 validation ≈ 0.303  ( 98%)
[ Info: [  8%] LOSS: training ≈ 0.3058 validation ≈ 0.3005 ( 98%)
[ Info: [  8%] LOSS: training ≈ 0.3039 validation ≈ 0.2981 ( 98%)
[ Info: [  9%] LOSS: training ≈ 0.3023 validation ≈ 0.296  ( 98%)
[ Info: [ 10%] LOSS: training ≈ 0.3007 validation ≈ 0.2939 ( 98%)
[ Info: [ 10%] LOSS: training ≈ 0.2993 validation ≈ 0.292  ( 98%)
[ Info: [ 10%] LOSS: training ≈ 0.2979 validation ≈ 0.2902 ( 97%)
[ Info: [ 11%] LOSS: training ≈ 0.2967 validation ≈ 0.2885 ( 97%)
[ Info: [ 12%] LOSS: training ≈ 0.2955 validation ≈ 0.2869 ( 97%)
[ Info: [ 12%] LOSS: training ≈ 0.2944 validation ≈ 0.2854 ( 97%)
[ Info: [ 12%] LOSS: training ≈ 0.2934 validation ≈ 0.2839 ( 97%)
[ Info: [ 13%] LOSS: training ≈ 0.2924 validation ≈ 0.2825 ( 97%)
[ Info: [ 14%] LOSS: training ≈ 0.2915 validation ≈ 0.2811 ( 96%)
[ Info: [ 14%] LOSS: training ≈ 0.2906 validation ≈ 0.2798 ( 96%)
[ Info: [ 14%] LOSS: training ≈ 0.2897 validation ≈ 0.2786 ( 96%)
[ Info: [ 15%] LOSS: training ≈ 0.2889 validation ≈ 0.2774 ( 96%)
[ Info: [ 16%] LOSS: training ≈ 0.2881 validation ≈ 0.2762 ( 96%)
[ Info: [ 16%] LOSS: training ≈ 0.2874 validation ≈ 0.2751 ( 96%)
[ Info: [ 16%] LOSS: training ≈ 0.2867 validation ≈ 0.2741 ( 96%)
[ Info: [ 17%] LOSS: training ≈ 0.286  validation ≈ 0.273  ( 95%)
[ Info: [ 18%] LOSS: training ≈ 0.2854 validation ≈ 0.272  ( 95%)
[ Info: [ 18%] LOSS: training ≈ 0.2847 validation ≈ 0.271  ( 95%)
[ Info: [ 18%] LOSS: training ≈ 0.2841 validation ≈ 0.2701 ( 95%)
[ Info: [ 19%] LOSS: training ≈ 0.2835 validation ≈ 0.2692 ( 95%)
[ Info: [ 20%] LOSS: training ≈ 0.283  validation ≈ 0.2683 ( 95%)
[ Info: [ 20%] LOSS: training ≈ 0.2824 validation ≈ 0.2675 ( 95%)
[ Info: [ 20%] LOSS: training ≈ 0.2819 validation ≈ 0.2666 ( 95%)
[ Info: [ 21%] LOSS: training ≈ 0.2814 validation ≈ 0.2658 ( 94%)
[ Info: [ 22%] LOSS: training ≈ 0.2809 validation ≈ 0.265  ( 94%)
[ Info: [ 22%] LOSS: training ≈ 0.2804 validation ≈ 0.2643 ( 94%)
[ Info: [ 22%] LOSS: training ≈ 0.28   validation ≈ 0.2635 ( 94%)
[ Info: [ 23%] LOSS: training ≈ 0.2795 validation ≈ 0.2628 ( 94%)
[ Info: [ 24%] LOSS: training ≈ 0.2791 validation ≈ 0.2621 ( 94%)
[ Info: [ 24%] LOSS: training ≈ 0.2787 validation ≈ 0.2614 ( 94%)
[ Info: [ 24%] LOSS: training ≈ 0.2783 validation ≈ 0.2608 ( 94%)
[ Info: [ 25%] LOSS: training ≈ 0.2779 validation ≈ 0.2601 ( 94%)
[ Info: [ 26%] LOSS: training ≈ 0.2775 validation ≈ 0.2595 ( 94%)
[ Info: [ 26%] LOSS: training ≈ 0.2771 validation ≈ 0.2589 ( 93%)
[ Info: [ 26%] LOSS: training ≈ 0.2768 validation ≈ 0.2583 ( 93%)
[ Info: [ 27%] LOSS: training ≈ 0.2764 validation ≈ 0.2577 ( 93%)
[ Info: [ 28%] LOSS: training ≈ 0.2761 validation ≈ 0.2572 ( 93%)
[ Info: [ 28%] LOSS: training ≈ 0.2758 validation ≈ 0.2566 ( 93%)
[ Info: [ 28%] LOSS: training ≈ 0.2754 validation ≈ 0.2561 ( 93%)
[ Info: [ 29%] LOSS: training ≈ 0.2751 validation ≈ 0.2556 ( 93%)
[ Info: [ 30%] LOSS: training ≈ 0.2748 validation ≈ 0.255  ( 93%)
[ Info: [ 30%] LOSS: training ≈ 0.2745 validation ≈ 0.2545 ( 93%)
[ Info: [ 30%] LOSS: training ≈ 0.2743 validation ≈ 0.2541 ( 93%)
[ Info: [ 31%] LOSS: training ≈ 0.274  validation ≈ 0.2536 ( 93%)
[ Info: [ 32%] LOSS: training ≈ 0.2737 validation ≈ 0.2531 ( 92%)
[ Info: [ 32%] LOSS: training ≈ 0.2734 validation ≈ 0.2527 ( 92%)
[ Info: [ 32%] LOSS: training ≈ 0.2732 validation ≈ 0.2522 ( 92%)
[ Info: [ 33%] LOSS: training ≈ 0.2729 validation ≈ 0.2518 ( 92%)
[ Info: [ 34%] LOSS: training ≈ 0.2727 validation ≈ 0.2514 ( 92%)
[ Info: [ 34%] LOSS: training ≈ 0.2725 validation ≈ 0.251  ( 92%)
[ Info: [ 34%] LOSS: training ≈ 0.2722 validation ≈ 0.2506 ( 92%)
[ Info: [ 35%] LOSS: training ≈ 0.272  validation ≈ 0.2502 ( 92%)
[ Info: [ 36%] LOSS: training ≈ 0.2718 validation ≈ 0.2498 ( 92%)
[ Info: [ 36%] LOSS: training ≈ 0.2716 validation ≈ 0.2494 ( 92%)
[ Info: [ 36%] LOSS: training ≈ 0.2714 validation ≈ 0.2491 ( 92%)
[ Info: [ 37%] LOSS: training ≈ 0.2712 validation ≈ 0.2487 ( 92%)
[ Info: [ 38%] LOSS: training ≈ 0.271  validation ≈ 0.2483 ( 92%)
[ Info: [ 38%] LOSS: training ≈ 0.2708 validation ≈ 0.248  ( 92%)
[ Info: [ 38%] LOSS: training ≈ 0.2706 validation ≈ 0.2477 ( 92%)
[ Info: [ 39%] LOSS: training ≈ 0.2704 validation ≈ 0.2473 ( 91%)
[ Info: [ 40%] LOSS: training ≈ 0.2702 validation ≈ 0.247  ( 91%)
[ Info: [ 40%] LOSS: training ≈ 0.2701 validation ≈ 0.2467 ( 91%)
[ Info: [ 40%] LOSS: training ≈ 0.2699 validation ≈ 0.2464 ( 91%)
[ Info: [ 41%] LOSS: training ≈ 0.2697 validation ≈ 0.2461 ( 91%)
[ Info: [ 42%] LOSS: training ≈ 0.2696 validation ≈ 0.2458 ( 91%)
[ Info: [ 42%] LOSS: training ≈ 0.2694 validation ≈ 0.2455 ( 91%)
[ Info: [ 42%] LOSS: training ≈ 0.2693 validation ≈ 0.2452 ( 91%)
[ Info: [ 43%] LOSS: training ≈ 0.2691 validation ≈ 0.245  ( 91%)
[ Info: [ 44%] LOSS: training ≈ 0.269  validation ≈ 0.2447 ( 91%)
[ Info: [ 44%] LOSS: training ≈ 0.2688 validation ≈ 0.2444 ( 91%)
[ Info: [ 44%] LOSS: training ≈ 0.2687 validation ≈ 0.2442 ( 91%)
[ Info: [ 45%] LOSS: training ≈ 0.2685 validation ≈ 0.2439 ( 91%)
[ Info: [ 46%] LOSS: training ≈ 0.2684 validation ≈ 0.2437 ( 91%)
[ Info: [ 46%] LOSS: training ≈ 0.2683 validation ≈ 0.2434 ( 91%)
[ Info: [ 46%] LOSS: training ≈ 0.2682 validation ≈ 0.2432 ( 91%)
[ Info: [ 47%] LOSS: training ≈ 0.268  validation ≈ 0.243  ( 91%)
[ Info: [ 48%] LOSS: training ≈ 0.2679 validation ≈ 0.2427 ( 91%)
[ Info: [ 48%] LOSS: training ≈ 0.2678 validation ≈ 0.2425 ( 91%)
[ Info: [ 48%] LOSS: training ≈ 0.2677 validation ≈ 0.2423 ( 91%)
[ Info: [ 49%] LOSS: training ≈ 0.2676 validation ≈ 0.2421 ( 90%)
[ Info: [ 50%] LOSS: training ≈ 0.2675 validation ≈ 0.2418 ( 90%)
[ Info: [ 50%] LOSS: training ≈ 0.2674 validation ≈ 0.2416 ( 90%)
[ Info: [ 50%] LOSS: training ≈ 0.2672 validation ≈ 0.2414 ( 90%)
[ Info: [ 51%] LOSS: training ≈ 0.2671 validation ≈ 0.2412 ( 90%)
[ Info: [ 52%] LOSS: training ≈ 0.267  validation ≈ 0.241  ( 90%)
[ Info: [ 52%] LOSS: training ≈ 0.2669 validation ≈ 0.2408 ( 90%)
[ Info: [ 52%] LOSS: training ≈ 0.2668 validation ≈ 0.2406 ( 90%)
[ Info: [ 53%] LOSS: training ≈ 0.2668 validation ≈ 0.2405 ( 90%)
[ Info: [ 54%] LOSS: training ≈ 0.2667 validation ≈ 0.2403 ( 90%)
[ Info: [ 54%] LOSS: training ≈ 0.2666 validation ≈ 0.2401 ( 90%)
[ Info: [ 55%] LOSS: training ≈ 0.2665 validation ≈ 0.2399 ( 90%)
[ Info: [ 55%] LOSS: training ≈ 0.2664 validation ≈ 0.2397 ( 90%)
[ Info: [ 56%] LOSS: training ≈ 0.2663 validation ≈ 0.2396 ( 90%)
[ Info: [ 56%] LOSS: training ≈ 0.2662 validation ≈ 0.2394 ( 90%)
[ Info: [ 56%] LOSS: training ≈ 0.2661 validation ≈ 0.2392 ( 90%)
[ Info: [ 57%] LOSS: training ≈ 0.2661 validation ≈ 0.2391 ( 90%)
[ Info: [ 57%] LOSS: training ≈ 0.266  validation ≈ 0.2389 ( 90%)
[ Info: [ 58%] LOSS: training ≈ 0.2659 validation ≈ 0.2388 ( 90%)
[ Info: [ 58%] LOSS: training ≈ 0.2658 validation ≈ 0.2386 ( 90%)
[ Info: [ 59%] LOSS: training ≈ 0.2658 validation ≈ 0.2385 ( 90%)
[ Info: [ 60%] LOSS: training ≈ 0.2657 validation ≈ 0.2383 ( 90%)
[ Info: [ 60%] LOSS: training ≈ 0.2656 validation ≈ 0.2382 ( 90%)
[ Info: [ 60%] LOSS: training ≈ 0.2656 validation ≈ 0.238  ( 90%)
[ Info: [ 61%] LOSS: training ≈ 0.2655 validation ≈ 0.2379 ( 90%)
[ Info: [ 62%] LOSS: training ≈ 0.2654 validation ≈ 0.2377 ( 90%)
[ Info: [ 62%] LOSS: training ≈ 0.2654 validation ≈ 0.2376 ( 90%)
[ Info: [ 62%] LOSS: training ≈ 0.2653 validation ≈ 0.2375 ( 90%)
[ Info: [ 63%] LOSS: training ≈ 0.2652 validation ≈ 0.2373 ( 89%)
[ Info: [ 64%] LOSS: training ≈ 0.2652 validation ≈ 0.2372 ( 89%)
[ Info: [ 64%] LOSS: training ≈ 0.2651 validation ≈ 0.2371 ( 89%)
[ Info: [ 64%] LOSS: training ≈ 0.2651 validation ≈ 0.237  ( 89%)
[ Info: [ 65%] LOSS: training ≈ 0.265  validation ≈ 0.2368 ( 89%)
[ Info: [ 66%] LOSS: training ≈ 0.2649 validation ≈ 0.2367 ( 89%)
[ Info: [ 66%] LOSS: training ≈ 0.2649 validation ≈ 0.2366 ( 89%)
[ Info: [ 66%] LOSS: training ≈ 0.2648 validation ≈ 0.2365 ( 89%)
[ Info: [ 67%] LOSS: training ≈ 0.2648 validation ≈ 0.2364 ( 89%)
[ Info: [ 68%] LOSS: training ≈ 0.2647 validation ≈ 0.2362 ( 89%)
[ Info: [ 68%] LOSS: training ≈ 0.2647 validation ≈ 0.2361 ( 89%)
[ Info: [ 68%] LOSS: training ≈ 0.2646 validation ≈ 0.236  ( 89%)
[ Info: [ 69%] LOSS: training ≈ 0.2646 validation ≈ 0.2359 ( 89%)
[ Info: [ 70%] LOSS: training ≈ 0.2645 validation ≈ 0.2358 ( 89%)
[ Info: [ 70%] LOSS: training ≈ 0.2645 validation ≈ 0.2357 ( 89%)
[ Info: [ 70%] LOSS: training ≈ 0.2644 validation ≈ 0.2356 ( 89%)
[ Info: [ 71%] LOSS: training ≈ 0.2644 validation ≈ 0.2355 ( 89%)
[ Info: [ 72%] LOSS: training ≈ 0.2643 validation ≈ 0.2354 ( 89%)
[ Info: [ 72%] LOSS: training ≈ 0.2643 validation ≈ 0.2353 ( 89%)
[ Info: [ 72%] LOSS: training ≈ 0.2643 validation ≈ 0.2352 ( 89%)
[ Info: [ 73%] LOSS: training ≈ 0.2642 validation ≈ 0.2351 ( 89%)
[ Info: [ 74%] LOSS: training ≈ 0.2642 validation ≈ 0.235  ( 89%)
[ Info: [ 74%] LOSS: training ≈ 0.2641 validation ≈ 0.2349 ( 89%)
[ Info: [ 74%] LOSS: training ≈ 0.2641 validation ≈ 0.2348 ( 89%)
[ Info: [ 75%] LOSS: training ≈ 0.2641 validation ≈ 0.2347 ( 89%)
[ Info: [ 76%] LOSS: training ≈ 0.264  validation ≈ 0.2346 ( 89%)
[ Info: [ 76%] LOSS: training ≈ 0.264  validation ≈ 0.2345 ( 89%)
[ Info: [ 76%] LOSS: training ≈ 0.2639 validation ≈ 0.2345 ( 89%)
[ Info: [ 77%] LOSS: training ≈ 0.2639 validation ≈ 0.2344 ( 89%)
[ Info: [ 78%] LOSS: training ≈ 0.2639 validation ≈ 0.2343 ( 89%)
[ Info: [ 78%] LOSS: training ≈ 0.2638 validation ≈ 0.2342 ( 89%)
[ Info: [ 78%] LOSS: training ≈ 0.2638 validation ≈ 0.2341 ( 89%)
[ Info: [ 79%] LOSS: training ≈ 0.2638 validation ≈ 0.234  ( 89%)
[ Info: [ 80%] LOSS: training ≈ 0.2637 validation ≈ 0.234  ( 89%)
[ Info: [ 80%] LOSS: training ≈ 0.2637 validation ≈ 0.2339 ( 89%)
[ Info: [ 80%] LOSS: training ≈ 0.2637 validation ≈ 0.2338 ( 89%)
[ Info: [ 81%] LOSS: training ≈ 0.2636 validation ≈ 0.2337 ( 89%)
[ Info: [ 82%] LOSS: training ≈ 0.2636 validation ≈ 0.2337 ( 89%)
[ Info: [ 82%] LOSS: training ≈ 0.2636 validation ≈ 0.2336 ( 89%)
[ Info: [ 82%] LOSS: training ≈ 0.2635 validation ≈ 0.2335 ( 89%)
[ Info: [ 83%] LOSS: training ≈ 0.2635 validation ≈ 0.2334 ( 89%)
[ Info: [ 84%] LOSS: training ≈ 0.2635 validation ≈ 0.2334 ( 89%)
[ Info: [ 84%] LOSS: training ≈ 0.2635 validation ≈ 0.2333 ( 89%)
[ Info: [ 84%] LOSS: training ≈ 0.2634 validation ≈ 0.2332 ( 89%)
[ Info: [ 85%] LOSS: training ≈ 0.2634 validation ≈ 0.2331 ( 89%)
[ Info: [ 86%] LOSS: training ≈ 0.2634 validation ≈ 0.2331 ( 88%)
[ Info: [ 86%] LOSS: training ≈ 0.2633 validation ≈ 0.233  ( 88%)
[ Info: [ 86%] LOSS: training ≈ 0.2633 validation ≈ 0.2329 ( 88%)
[ Info: [ 87%] LOSS: training ≈ 0.2633 validation ≈ 0.2329 ( 88%)
[ Info: [ 88%] LOSS: training ≈ 0.2633 validation ≈ 0.2328 ( 88%)
[ Info: [ 88%] LOSS: training ≈ 0.2632 validation ≈ 0.2328 ( 88%)
[ Info: [ 88%] LOSS: training ≈ 0.2632 validation ≈ 0.2327 ( 88%)
[ Info: [ 89%] LOSS: training ≈ 0.2632 validation ≈ 0.2326 ( 88%)
[ Info: [ 90%] LOSS: training ≈ 0.2632 validation ≈ 0.2326 ( 88%)
[ Info: [ 90%] LOSS: training ≈ 0.2631 validation ≈ 0.2325 ( 88%)
[ Info: [ 90%] LOSS: training ≈ 0.2631 validation ≈ 0.2324 ( 88%)
[ Info: [ 91%] LOSS: training ≈ 0.2631 validation ≈ 0.2324 ( 88%)
[ Info: [ 92%] LOSS: training ≈ 0.2631 validation ≈ 0.2323 ( 88%)
[ Info: [ 92%] LOSS: training ≈ 0.2631 validation ≈ 0.2323 ( 88%)
[ Info: [ 92%] LOSS: training ≈ 0.263  validation ≈ 0.2322 ( 88%)
[ Info: [ 93%] LOSS: training ≈ 0.263  validation ≈ 0.2322 ( 88%)
[ Info: [ 94%] LOSS: training ≈ 0.263  validation ≈ 0.2321 ( 88%)
[ Info: [ 94%] LOSS: training ≈ 0.263  validation ≈ 0.232  ( 88%)
[ Info: [ 94%] LOSS: training ≈ 0.263  validation ≈ 0.232  ( 88%)
[ Info: [ 95%] LOSS: training ≈ 0.2629 validation ≈ 0.2319 ( 88%)
[ Info: [ 96%] LOSS: training ≈ 0.2629 validation ≈ 0.2319 ( 88%)
[ Info: [ 96%] LOSS: training ≈ 0.2629 validation ≈ 0.2318 ( 88%)
[ Info: [ 96%] LOSS: training ≈ 0.2629 validation ≈ 0.2318 ( 88%)
[ Info: [ 97%] LOSS: training ≈ 0.2629 validation ≈ 0.2317 ( 88%)
[ Info: [ 98%] LOSS: training ≈ 0.2628 validation ≈ 0.2317 ( 88%)
[ Info: [ 98%] LOSS: training ≈ 0.2628 validation ≈ 0.2316 ( 88%)
[ Info: [ 98%] LOSS: training ≈ 0.2628 validation ≈ 0.2316 ( 88%)
[ Info: [ 99%] LOSS: training ≈ 0.2628 validation ≈ 0.2315 ( 88%)
[ Info: [100%] LOSS: training ≈ 0.2628 validation ≈ 0.2315 ( 88%)
[ Info: [100%] LOSS: training ≈ 0.2627 validation ≈ 0.2314 ( 88%)
[ 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. ≈ 0.467
[ Info: Optimal var. pool: [1, 12, 2]
┌ 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. ≈ 0.779
[ Info: [ 2 vars.] MCC val. ≈ 0.814
[ Info: Optimal var. pool: [8, 7]
┌ 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. ≈ 0.573
[ Info: [17 vars.] MCC val. ≈ 0.752
[ Info: [16 vars.] MCC val. ≈ 0.773
[ Info: [15 vars.] MCC val. ≈ 0.794
[ Info: Optimal var. pool: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 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. ≈ 0.76
[ Info: [ 7 vars.] MCC val. ≈ 0.781
[ Info: Optimal var. pool: [1, 2, 3, 5, 6, 7, 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. ≈ 0.476
[ 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. ≈ 0.759
[ Info: [ 2 vars.] MCC val. ≈ 0.78
[ Info: Optimal var. pool: [8, 7]
Test Summary: | Pass  Total      Time
Package       |  297    297  19m00.7s
     Testing SDeMo tests passed 

Testing completed after 1191.88s

PkgEval succeeded after 1251.11s