Package evaluation to test SDeMo on Julia 1.14.0-DEV.1720 (f38c537ec6*) started at 2026-02-15T17:48:29.463


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

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

Set-up completed after 12.54s


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

Installing SDeMo...
   Resolving package versions...
    Updating `~/.julia/environments/v1.14/Project.toml`
  [3e5feb82] + SDeMo v1.7.1
    Updating `~/.julia/environments/v1.14/Manifest.toml`
  [66dad0bd] + AliasTables v1.1.3
  [7d9fca2a] + Arpack v0.5.4
  [9a962f9c] + DataAPI v1.16.0
  [864edb3b] + DataStructures v0.19.3
  [31c24e10] + Distributions v0.25.123
  [ffbed154] + DocStringExtensions v0.9.5
  [1a297f60] + FillArrays v1.16.0
  [34004b35] + HypergeometricFunctions v0.3.28
  [92d709cd] + IrrationalConstants v0.2.6
  [692b3bcd] + JLLWrappers v1.7.1
  [682c06a0] + JSON v1.4.0
  [2ab3a3ac] + LogExpFunctions v0.3.29
  [e1d29d7a] + Missings v1.2.0
  [6f286f6a] + MultivariateStats v0.10.3
  [bac558e1] + OrderedCollections v1.8.1
  [90014a1f] + PDMats v0.11.37
  [69de0a69] + Parsers v2.8.3
  [aea7be01] + PrecompileTools v1.3.3
  [21216c6a] + Preferences v1.5.1
  [43287f4e] + PtrArrays v1.3.0
  [1fd47b50] + QuadGK v2.11.2
  [189a3867] + Reexport v1.2.2
  [79098fc4] + Rmath v0.9.0
  [3e5feb82] + SDeMo v1.7.1
  [a2af1166] + SortingAlgorithms v1.2.2
  [276daf66] + SpecialFunctions v2.7.1
  [10745b16] + Statistics v1.11.1
  [82ae8749] + StatsAPI v1.8.0
  [2913bbd2] + StatsBase v0.34.10
  [4c63d2b9] + StatsFuns v1.5.2
  [ec057cc2] + StructUtils v2.6.3
  [1c621080] + TestItems v1.0.0
⌅ [68821587] + Arpack_jll v3.5.2+0
  [efe28fd5] + OpenSpecFun_jll v0.5.6+0
  [f50d1b31] + Rmath_jll v0.5.1+0
  [56f22d72] + Artifacts v1.11.0
  [ade2ca70] + Dates v1.11.0
  [8f399da3] + Libdl v1.11.0
  [37e2e46d] + LinearAlgebra v1.13.0
  [56ddb016] + Logging v1.11.0
  [de0858da] + Printf v1.11.0
  [9a3f8284] + Random v1.11.0
  [ea8e919c] + SHA v1.0.0
  [9e88b42a] + Serialization v1.11.0
  [2f01184e] + SparseArrays v1.13.0
  [4607b0f0] + SuiteSparse
  [fa267f1f] + TOML v1.0.3
  [cf7118a7] + UUIDs v1.11.0
  [4ec0a83e] + Unicode v1.11.0
  [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1
  [4536629a] + OpenBLAS_jll v0.3.30+0
  [05823500] + OpenLibm_jll v0.8.7+0
  [bea87d4a] + SuiteSparse_jll v7.10.1+0
  [8e850b90] + libblastrampoline_jll v5.15.0+0
        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 5.25s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...
Precompiling packages...
   4210.8 ms  ✓ MultivariateStats
   5317.7 ms  ✓ SDeMo
  2 dependencies successfully precompiled in 10 seconds. 74 already precompiled.

Precompilation completed after 32.29s


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

     Testing SDeMo
      Status `/tmp/jl_3Am4OQ/Project.toml`
  [3e5feb82] SDeMo v1.7.1
  [10745b16] Statistics v1.11.1
  [f8b46487] TestItemRunner v1.1.4
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_3Am4OQ/Manifest.toml`
  [66dad0bd] AliasTables v1.1.3
  [7d9fca2a] Arpack v0.5.4
  [9a962f9c] DataAPI v1.16.0
  [864edb3b] DataStructures v0.19.3
  [31c24e10] Distributions v0.25.123
  [ffbed154] DocStringExtensions v0.9.5
  [1a297f60] FillArrays v1.16.0
  [34004b35] HypergeometricFunctions v0.3.28
  [92d709cd] IrrationalConstants v0.2.6
  [692b3bcd] JLLWrappers v1.7.1
  [682c06a0] JSON v1.4.0
  [2ab3a3ac] LogExpFunctions v0.3.29
  [e1d29d7a] Missings v1.2.0
  [6f286f6a] MultivariateStats v0.10.3
  [bac558e1] OrderedCollections v1.8.1
  [90014a1f] PDMats v0.11.37
  [69de0a69] Parsers v2.8.3
  [aea7be01] PrecompileTools v1.3.3
  [21216c6a] Preferences v1.5.1
  [43287f4e] PtrArrays v1.3.0
  [1fd47b50] QuadGK v2.11.2
  [189a3867] Reexport v1.2.2
  [79098fc4] Rmath v0.9.0
  [3e5feb82] SDeMo v1.7.1
  [a2af1166] SortingAlgorithms v1.2.2
  [276daf66] SpecialFunctions v2.7.1
  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.8.0
  [2913bbd2] StatsBase v0.34.10
  [4c63d2b9] StatsFuns v1.5.2
  [ec057cc2] StructUtils v2.6.3
  [f8b46487] TestItemRunner v1.1.4
  [1c621080] TestItems v1.0.0
⌅ [68821587] Arpack_jll v3.5.2+0
  [efe28fd5] OpenSpecFun_jll v0.5.6+0
  [f50d1b31] Rmath_jll v0.5.1+0
  [0dad84c5] ArgTools v1.1.2
  [56f22d72] Artifacts v1.11.0
  [2a0f44e3] Base64 v1.11.0
  [ade2ca70] Dates v1.11.0
  [f43a241f] Downloads v1.7.0
  [7b1f6079] FileWatching v1.11.0
  [b77e0a4c] InteractiveUtils v1.11.0
  [ac6e5ff7] JuliaSyntaxHighlighting v1.13.0
  [b27032c2] LibCURL v1.0.0
  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.13.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [ca575930] NetworkOptions v1.3.0
  [44cfe95a] Pkg v1.14.0
  [de0858da] Printf v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v1.0.0
  [9e88b42a] Serialization v1.11.0
  [2f01184e] SparseArrays v1.13.0
  [f489334b] StyledStrings v1.13.0
  [4607b0f0] SuiteSparse
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [8dfed614] Test v1.11.0
  [cf7118a7] UUIDs v1.11.0
  [4ec0a83e] Unicode v1.11.0
  [e66e0078] CompilerSupportLibraries_jll v1.3.0+1
  [deac9b47] LibCURL_jll v8.18.0+0
  [e37daf67] LibGit2_jll v1.9.2+0
  [29816b5a] LibSSH2_jll v1.11.3+1
  [14a3606d] MozillaCACerts_jll v2025.12.2
  [4536629a] OpenBLAS_jll v0.3.30+0
  [05823500] OpenLibm_jll v0.8.7+0
  [458c3c95] OpenSSL_jll v3.5.5+0
  [efcefdf7] PCRE2_jll v10.47.0+0
  [bea87d4a] SuiteSparse_jll v7.10.1+0
  [83775a58] Zlib_jll v1.3.1+2
  [3161d3a3] Zstd_jll v1.5.7+1
  [8e850b90] libblastrampoline_jll v5.15.0+0
  [8e850ede] nghttp2_jll v1.68.0+1
  [3f19e933] p7zip_jll v17.7.0+0
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading.
     Testing Running tests...
[ Info: [  0%] LOSS: training ≈ 0.4961 validation ≈ 0.4932 ( 99%)
[ Info: [  1%] LOSS: training ≈ 0.4209 validation ≈ 0.4287 (102%)
[ Info: [  2%] LOSS: training ≈ 0.3838 validation ≈ 0.3973 (104%)
[ Info: [  2%] LOSS: training ≈ 0.3616 validation ≈ 0.3789 (105%)
[ Info: [  2%] LOSS: training ≈ 0.3468 validation ≈ 0.3669 (106%)
[ Info: [  3%] LOSS: training ≈ 0.3361 validation ≈ 0.3584 (107%)
[ Info: [  4%] LOSS: training ≈ 0.3279 validation ≈ 0.352  (107%)
[ Info: [  4%] LOSS: training ≈ 0.3213 validation ≈ 0.347  (108%)
[ Info: [  4%] LOSS: training ≈ 0.316  validation ≈ 0.343  (109%)
[ Info: [  5%] LOSS: training ≈ 0.3115 validation ≈ 0.3396 (109%)
[ Info: [  6%] LOSS: training ≈ 0.3077 validation ≈ 0.3367 (109%)
[ Info: [  6%] LOSS: training ≈ 0.3044 validation ≈ 0.3342 (110%)
[ Info: [  6%] LOSS: training ≈ 0.3015 validation ≈ 0.332  (110%)
[ Info: [  7%] LOSS: training ≈ 0.2989 validation ≈ 0.3301 (110%)
[ Info: [  8%] LOSS: training ≈ 0.2965 validation ≈ 0.3283 (111%)
[ Info: [  8%] LOSS: training ≈ 0.2944 validation ≈ 0.3266 (111%)
[ Info: [  8%] LOSS: training ≈ 0.2925 validation ≈ 0.3251 (111%)
[ Info: [  9%] LOSS: training ≈ 0.2907 validation ≈ 0.3237 (111%)
[ Info: [ 10%] LOSS: training ≈ 0.2891 validation ≈ 0.3224 (112%)
[ Info: [ 10%] LOSS: training ≈ 0.2876 validation ≈ 0.3212 (112%)
[ Info: [ 10%] LOSS: training ≈ 0.2862 validation ≈ 0.32   (112%)
[ Info: [ 11%] LOSS: training ≈ 0.2849 validation ≈ 0.3189 (112%)
[ Info: [ 12%] LOSS: training ≈ 0.2836 validation ≈ 0.3178 (112%)
[ Info: [ 12%] LOSS: training ≈ 0.2825 validation ≈ 0.3168 (112%)
[ Info: [ 12%] LOSS: training ≈ 0.2814 validation ≈ 0.3158 (112%)
[ Info: [ 13%] LOSS: training ≈ 0.2804 validation ≈ 0.3149 (112%)
[ Info: [ 14%] LOSS: training ≈ 0.2794 validation ≈ 0.314  (112%)
[ Info: [ 14%] LOSS: training ≈ 0.2784 validation ≈ 0.3131 (112%)
[ Info: [ 14%] LOSS: training ≈ 0.2775 validation ≈ 0.3123 (113%)
[ Info: [ 15%] LOSS: training ≈ 0.2767 validation ≈ 0.3115 (113%)
[ Info: [ 16%] LOSS: training ≈ 0.2759 validation ≈ 0.3107 (113%)
[ Info: [ 16%] LOSS: training ≈ 0.2751 validation ≈ 0.3099 (113%)
[ Info: [ 16%] LOSS: training ≈ 0.2744 validation ≈ 0.3092 (113%)
[ Info: [ 17%] LOSS: training ≈ 0.2737 validation ≈ 0.3085 (113%)
[ Info: [ 18%] LOSS: training ≈ 0.273  validation ≈ 0.3078 (113%)
[ Info: [ 18%] LOSS: training ≈ 0.2723 validation ≈ 0.3071 (113%)
[ Info: [ 18%] LOSS: training ≈ 0.2717 validation ≈ 0.3064 (113%)
[ Info: [ 19%] LOSS: training ≈ 0.271  validation ≈ 0.3058 (113%)
[ Info: [ 20%] LOSS: training ≈ 0.2705 validation ≈ 0.3052 (113%)
[ Info: [ 20%] LOSS: training ≈ 0.2699 validation ≈ 0.3046 (113%)
[ Info: [ 20%] LOSS: training ≈ 0.2693 validation ≈ 0.304  (113%)
[ Info: [ 21%] LOSS: training ≈ 0.2688 validation ≈ 0.3034 (113%)
[ Info: [ 22%] LOSS: training ≈ 0.2683 validation ≈ 0.3028 (113%)
[ Info: [ 22%] LOSS: training ≈ 0.2678 validation ≈ 0.3023 (113%)
[ Info: [ 22%] LOSS: training ≈ 0.2673 validation ≈ 0.3018 (113%)
[ Info: [ 23%] LOSS: training ≈ 0.2668 validation ≈ 0.3012 (113%)
[ Info: [ 24%] LOSS: training ≈ 0.2664 validation ≈ 0.3007 (113%)
[ Info: [ 24%] LOSS: training ≈ 0.2659 validation ≈ 0.3002 (113%)
[ Info: [ 24%] LOSS: training ≈ 0.2655 validation ≈ 0.2998 (113%)
[ Info: [ 25%] LOSS: training ≈ 0.2651 validation ≈ 0.2993 (113%)
[ Info: [ 26%] LOSS: training ≈ 0.2647 validation ≈ 0.2988 (113%)
[ Info: [ 26%] LOSS: training ≈ 0.2643 validation ≈ 0.2984 (113%)
[ Info: [ 26%] LOSS: training ≈ 0.2639 validation ≈ 0.2979 (113%)
[ Info: [ 27%] LOSS: training ≈ 0.2635 validation ≈ 0.2975 (113%)
[ Info: [ 28%] LOSS: training ≈ 0.2631 validation ≈ 0.2971 (113%)
[ Info: [ 28%] LOSS: training ≈ 0.2628 validation ≈ 0.2967 (113%)
[ Info: [ 28%] LOSS: training ≈ 0.2624 validation ≈ 0.2963 (113%)
[ Info: [ 29%] LOSS: training ≈ 0.2621 validation ≈ 0.2959 (113%)
[ Info: [ 30%] LOSS: training ≈ 0.2618 validation ≈ 0.2955 (113%)
[ Info: [ 30%] LOSS: training ≈ 0.2615 validation ≈ 0.2952 (113%)
[ Info: [ 30%] LOSS: training ≈ 0.2611 validation ≈ 0.2948 (113%)
[ Info: [ 31%] LOSS: training ≈ 0.2608 validation ≈ 0.2945 (113%)
[ Info: [ 32%] LOSS: training ≈ 0.2605 validation ≈ 0.2941 (113%)
[ Info: [ 32%] LOSS: training ≈ 0.2603 validation ≈ 0.2938 (113%)
[ Info: [ 32%] LOSS: training ≈ 0.26   validation ≈ 0.2935 (113%)
[ Info: [ 33%] LOSS: training ≈ 0.2597 validation ≈ 0.2932 (113%)
[ Info: [ 34%] LOSS: training ≈ 0.2594 validation ≈ 0.2928 (113%)
[ Info: [ 34%] LOSS: training ≈ 0.2592 validation ≈ 0.2925 (113%)
[ Info: [ 34%] LOSS: training ≈ 0.2589 validation ≈ 0.2922 (113%)
[ Info: [ 35%] LOSS: training ≈ 0.2587 validation ≈ 0.292  (113%)
[ Info: [ 36%] LOSS: training ≈ 0.2584 validation ≈ 0.2917 (113%)
[ Info: [ 36%] LOSS: training ≈ 0.2582 validation ≈ 0.2914 (113%)
[ Info: [ 36%] LOSS: training ≈ 0.258  validation ≈ 0.2911 (113%)
[ Info: [ 37%] LOSS: training ≈ 0.2578 validation ≈ 0.2909 (113%)
[ Info: [ 38%] LOSS: training ≈ 0.2575 validation ≈ 0.2906 (113%)
[ Info: [ 38%] LOSS: training ≈ 0.2573 validation ≈ 0.2904 (113%)
[ Info: [ 38%] LOSS: training ≈ 0.2571 validation ≈ 0.2901 (113%)
[ Info: [ 39%] LOSS: training ≈ 0.2569 validation ≈ 0.2899 (113%)
[ Info: [ 40%] LOSS: training ≈ 0.2567 validation ≈ 0.2897 (113%)
[ Info: [ 40%] LOSS: training ≈ 0.2565 validation ≈ 0.2895 (113%)
[ Info: [ 40%] LOSS: training ≈ 0.2563 validation ≈ 0.2892 (113%)
[ Info: [ 41%] LOSS: training ≈ 0.2561 validation ≈ 0.289  (113%)
[ Info: [ 42%] LOSS: training ≈ 0.256  validation ≈ 0.2888 (113%)
[ Info: [ 42%] LOSS: training ≈ 0.2558 validation ≈ 0.2886 (113%)
[ Info: [ 42%] LOSS: training ≈ 0.2556 validation ≈ 0.2884 (113%)
[ Info: [ 43%] LOSS: training ≈ 0.2554 validation ≈ 0.2882 (113%)
[ Info: [ 44%] LOSS: training ≈ 0.2553 validation ≈ 0.288  (113%)
[ Info: [ 44%] LOSS: training ≈ 0.2551 validation ≈ 0.2878 (113%)
[ Info: [ 44%] LOSS: training ≈ 0.2549 validation ≈ 0.2877 (113%)
[ Info: [ 45%] LOSS: training ≈ 0.2548 validation ≈ 0.2875 (113%)
[ Info: [ 46%] LOSS: training ≈ 0.2546 validation ≈ 0.2873 (113%)
[ Info: [ 46%] LOSS: training ≈ 0.2545 validation ≈ 0.2872 (113%)
[ Info: [ 46%] LOSS: training ≈ 0.2543 validation ≈ 0.287  (113%)
[ Info: [ 47%] LOSS: training ≈ 0.2542 validation ≈ 0.2868 (113%)
[ Info: [ 48%] LOSS: training ≈ 0.2541 validation ≈ 0.2867 (113%)
[ Info: [ 48%] LOSS: training ≈ 0.2539 validation ≈ 0.2865 (113%)
[ Info: [ 48%] LOSS: training ≈ 0.2538 validation ≈ 0.2864 (113%)
[ Info: [ 49%] LOSS: training ≈ 0.2537 validation ≈ 0.2862 (113%)
[ Info: [ 50%] LOSS: training ≈ 0.2535 validation ≈ 0.2861 (113%)
[ Info: [ 50%] LOSS: training ≈ 0.2534 validation ≈ 0.286  (113%)
[ Info: [ 50%] LOSS: training ≈ 0.2533 validation ≈ 0.2858 (113%)
[ Info: [ 51%] LOSS: training ≈ 0.2532 validation ≈ 0.2857 (113%)
[ Info: [ 52%] LOSS: training ≈ 0.253  validation ≈ 0.2856 (113%)
[ Info: [ 52%] LOSS: training ≈ 0.2529 validation ≈ 0.2854 (113%)
[ Info: [ 52%] LOSS: training ≈ 0.2528 validation ≈ 0.2853 (113%)
[ Info: [ 53%] LOSS: training ≈ 0.2527 validation ≈ 0.2852 (113%)
[ Info: [ 54%] LOSS: training ≈ 0.2526 validation ≈ 0.2851 (113%)
[ Info: [ 54%] LOSS: training ≈ 0.2525 validation ≈ 0.285  (113%)
[ Info: [ 55%] LOSS: training ≈ 0.2524 validation ≈ 0.2849 (113%)
[ Info: [ 55%] LOSS: training ≈ 0.2523 validation ≈ 0.2847 (113%)
[ Info: [ 56%] LOSS: training ≈ 0.2522 validation ≈ 0.2846 (113%)
[ Info: [ 56%] LOSS: training ≈ 0.2521 validation ≈ 0.2845 (113%)
[ Info: [ 56%] LOSS: training ≈ 0.252  validation ≈ 0.2844 (113%)
[ Info: [ 57%] LOSS: training ≈ 0.2519 validation ≈ 0.2843 (113%)
[ Info: [ 57%] LOSS: training ≈ 0.2518 validation ≈ 0.2842 (113%)
[ Info: [ 58%] LOSS: training ≈ 0.2517 validation ≈ 0.2841 (113%)
[ Info: [ 58%] LOSS: training ≈ 0.2516 validation ≈ 0.2841 (113%)
[ Info: [ 59%] LOSS: training ≈ 0.2515 validation ≈ 0.284  (113%)
[ Info: [ 60%] LOSS: training ≈ 0.2514 validation ≈ 0.2839 (113%)
[ Info: [ 60%] LOSS: training ≈ 0.2513 validation ≈ 0.2838 (113%)
[ Info: [ 60%] LOSS: training ≈ 0.2513 validation ≈ 0.2837 (113%)
[ Info: [ 61%] LOSS: training ≈ 0.2512 validation ≈ 0.2836 (113%)
[ Info: [ 62%] LOSS: training ≈ 0.2511 validation ≈ 0.2835 (113%)
[ Info: [ 62%] LOSS: training ≈ 0.251  validation ≈ 0.2835 (113%)
[ Info: [ 62%] LOSS: training ≈ 0.2509 validation ≈ 0.2834 (113%)
[ Info: [ 63%] LOSS: training ≈ 0.2509 validation ≈ 0.2833 (113%)
[ Info: [ 64%] LOSS: training ≈ 0.2508 validation ≈ 0.2832 (113%)
[ Info: [ 64%] LOSS: training ≈ 0.2507 validation ≈ 0.2832 (113%)
[ Info: [ 64%] LOSS: training ≈ 0.2507 validation ≈ 0.2831 (113%)
[ Info: [ 65%] LOSS: training ≈ 0.2506 validation ≈ 0.283  (113%)
[ Info: [ 66%] LOSS: training ≈ 0.2505 validation ≈ 0.283  (113%)
[ Info: [ 66%] LOSS: training ≈ 0.2504 validation ≈ 0.2829 (113%)
[ Info: [ 66%] LOSS: training ≈ 0.2504 validation ≈ 0.2828 (113%)
[ Info: [ 67%] LOSS: training ≈ 0.2503 validation ≈ 0.2828 (113%)
[ Info: [ 68%] LOSS: training ≈ 0.2502 validation ≈ 0.2827 (113%)
[ Info: [ 68%] LOSS: training ≈ 0.2502 validation ≈ 0.2826 (113%)
[ Info: [ 68%] LOSS: training ≈ 0.2501 validation ≈ 0.2826 (113%)
[ Info: [ 69%] LOSS: training ≈ 0.2501 validation ≈ 0.2825 (113%)
[ Info: [ 70%] LOSS: training ≈ 0.25   validation ≈ 0.2825 (113%)
[ Info: [ 70%] LOSS: training ≈ 0.2499 validation ≈ 0.2824 (113%)
[ Info: [ 70%] LOSS: training ≈ 0.2499 validation ≈ 0.2824 (113%)
[ Info: [ 71%] LOSS: training ≈ 0.2498 validation ≈ 0.2823 (113%)
[ Info: [ 72%] LOSS: training ≈ 0.2498 validation ≈ 0.2823 (113%)
[ Info: [ 72%] LOSS: training ≈ 0.2497 validation ≈ 0.2822 (113%)
[ Info: [ 72%] LOSS: training ≈ 0.2497 validation ≈ 0.2822 (113%)
[ Info: [ 73%] LOSS: training ≈ 0.2496 validation ≈ 0.2821 (113%)
[ Info: [ 74%] LOSS: training ≈ 0.2496 validation ≈ 0.2821 (113%)
[ Info: [ 74%] LOSS: training ≈ 0.2495 validation ≈ 0.282  (113%)
[ Info: [ 74%] LOSS: training ≈ 0.2495 validation ≈ 0.282  (113%)
[ Info: [ 75%] LOSS: training ≈ 0.2494 validation ≈ 0.2819 (113%)
[ Info: [ 76%] LOSS: training ≈ 0.2494 validation ≈ 0.2819 (113%)
[ Info: [ 76%] LOSS: training ≈ 0.2493 validation ≈ 0.2819 (113%)
[ Info: [ 76%] LOSS: training ≈ 0.2493 validation ≈ 0.2818 (113%)
[ Info: [ 77%] LOSS: training ≈ 0.2492 validation ≈ 0.2818 (113%)
[ Info: [ 78%] LOSS: training ≈ 0.2492 validation ≈ 0.2817 (113%)
[ Info: [ 78%] LOSS: training ≈ 0.2491 validation ≈ 0.2817 (113%)
[ Info: [ 78%] LOSS: training ≈ 0.2491 validation ≈ 0.2817 (113%)
[ Info: [ 79%] LOSS: training ≈ 0.249  validation ≈ 0.2816 (113%)
[ Info: [ 80%] LOSS: training ≈ 0.249  validation ≈ 0.2816 (113%)
[ Info: [ 80%] LOSS: training ≈ 0.249  validation ≈ 0.2815 (113%)
[ Info: [ 80%] LOSS: training ≈ 0.2489 validation ≈ 0.2815 (113%)
[ Info: [ 81%] LOSS: training ≈ 0.2489 validation ≈ 0.2815 (113%)
[ Info: [ 82%] LOSS: training ≈ 0.2488 validation ≈ 0.2814 (113%)
[ Info: [ 82%] LOSS: training ≈ 0.2488 validation ≈ 0.2814 (113%)
[ Info: [ 82%] LOSS: training ≈ 0.2488 validation ≈ 0.2814 (113%)
[ Info: [ 83%] LOSS: training ≈ 0.2487 validation ≈ 0.2814 (113%)
[ Info: [ 84%] LOSS: training ≈ 0.2487 validation ≈ 0.2813 (113%)
[ Info: [ 84%] LOSS: training ≈ 0.2486 validation ≈ 0.2813 (113%)
[ Info: [ 84%] LOSS: training ≈ 0.2486 validation ≈ 0.2813 (113%)
[ Info: [ 85%] LOSS: training ≈ 0.2486 validation ≈ 0.2812 (113%)
[ Info: [ 86%] LOSS: training ≈ 0.2485 validation ≈ 0.2812 (113%)
[ Info: [ 86%] LOSS: training ≈ 0.2485 validation ≈ 0.2812 (113%)
[ Info: [ 86%] LOSS: training ≈ 0.2485 validation ≈ 0.2812 (113%)
[ Info: [ 87%] LOSS: training ≈ 0.2484 validation ≈ 0.2811 (113%)
[ Info: [ 88%] LOSS: training ≈ 0.2484 validation ≈ 0.2811 (113%)
[ Info: [ 88%] LOSS: training ≈ 0.2484 validation ≈ 0.2811 (113%)
[ Info: [ 88%] LOSS: training ≈ 0.2483 validation ≈ 0.2811 (113%)
[ Info: [ 89%] LOSS: training ≈ 0.2483 validation ≈ 0.281  (113%)
[ Info: [ 90%] LOSS: training ≈ 0.2483 validation ≈ 0.281  (113%)
[ Info: [ 90%] LOSS: training ≈ 0.2482 validation ≈ 0.281  (113%)
[ Info: [ 90%] LOSS: training ≈ 0.2482 validation ≈ 0.281  (113%)
[ Info: [ 91%] LOSS: training ≈ 0.2482 validation ≈ 0.2809 (113%)
[ Info: [ 92%] LOSS: training ≈ 0.2481 validation ≈ 0.2809 (113%)
[ Info: [ 92%] LOSS: training ≈ 0.2481 validation ≈ 0.2809 (113%)
[ Info: [ 92%] LOSS: training ≈ 0.2481 validation ≈ 0.2809 (113%)
[ Info: [ 93%] LOSS: training ≈ 0.2481 validation ≈ 0.2809 (113%)
[ Info: [ 94%] LOSS: training ≈ 0.248  validation ≈ 0.2808 (113%)
[ Info: [ 94%] LOSS: training ≈ 0.248  validation ≈ 0.2808 (113%)
[ Info: [ 94%] LOSS: training ≈ 0.248  validation ≈ 0.2808 (113%)
[ Info: [ 95%] LOSS: training ≈ 0.2479 validation ≈ 0.2808 (113%)
[ Info: [ 96%] LOSS: training ≈ 0.2479 validation ≈ 0.2808 (113%)
[ Info: [ 96%] LOSS: training ≈ 0.2479 validation ≈ 0.2807 (113%)
[ Info: [ 96%] LOSS: training ≈ 0.2479 validation ≈ 0.2807 (113%)
[ Info: [ 97%] LOSS: training ≈ 0.2478 validation ≈ 0.2807 (113%)
[ Info: [ 98%] LOSS: training ≈ 0.2478 validation ≈ 0.2807 (113%)
[ Info: [ 98%] LOSS: training ≈ 0.2478 validation ≈ 0.2807 (113%)
[ Info: [ 98%] LOSS: training ≈ 0.2478 validation ≈ 0.2807 (113%)
[ Info: [ 99%] LOSS: training ≈ 0.2477 validation ≈ 0.2806 (113%)
[ Info: [100%] LOSS: training ≈ 0.2477 validation ≈ 0.2806 (113%)
[ Info: [100%] LOSS: training ≈ 0.2477 validation ≈ 0.2806 (113%)
[ Info: [  0%] LOSS: training ≈ 0.4747
[ Info: [  1%] LOSS: training ≈ 0.4038
[ Info: [  2%] LOSS: training ≈ 0.371 
[ Info: [  2%] LOSS: training ≈ 0.352 
[ Info: [  2%] LOSS: training ≈ 0.3394
[ Info: [  3%] LOSS: training ≈ 0.3303
[ Info: [  4%] LOSS: training ≈ 0.3233
[ Info: [  4%] LOSS: training ≈ 0.3178
[ Info: [  4%] LOSS: training ≈ 0.3132
[ Info: [  5%] LOSS: training ≈ 0.3093
[ Info: [  6%] LOSS: training ≈ 0.3059
[ Info: [  6%] LOSS: training ≈ 0.303 
[ Info: [  6%] LOSS: training ≈ 0.3004
[ Info: [  7%] LOSS: training ≈ 0.298 
[ Info: [  8%] LOSS: training ≈ 0.2959
[ Info: [  8%] LOSS: training ≈ 0.2939
[ Info: [  8%] LOSS: training ≈ 0.2921
[ Info: [  9%] LOSS: training ≈ 0.2905
[ Info: [ 10%] LOSS: training ≈ 0.289 
[ Info: [ 10%] LOSS: training ≈ 0.2875
[ Info: [ 10%] LOSS: training ≈ 0.2862
[ Info: [ 11%] LOSS: training ≈ 0.2849
[ Info: [ 12%] LOSS: training ≈ 0.2838
[ Info: [ 12%] LOSS: training ≈ 0.2826
[ Info: [ 12%] LOSS: training ≈ 0.2816
[ Info: [ 13%] LOSS: training ≈ 0.2806
[ Info: [ 14%] LOSS: training ≈ 0.2796
[ Info: [ 14%] LOSS: training ≈ 0.2787
[ Info: [ 14%] LOSS: training ≈ 0.2779
[ Info: [ 15%] LOSS: training ≈ 0.277 
[ Info: [ 16%] LOSS: training ≈ 0.2763
[ Info: [ 16%] LOSS: training ≈ 0.2755
[ Info: [ 16%] LOSS: training ≈ 0.2748
[ Info: [ 17%] LOSS: training ≈ 0.2741
[ Info: [ 18%] LOSS: training ≈ 0.2734
[ Info: [ 18%] LOSS: training ≈ 0.2728
[ Info: [ 18%] LOSS: training ≈ 0.2722
[ Info: [ 19%] LOSS: training ≈ 0.2716
[ Info: [ 20%] LOSS: training ≈ 0.271 
[ Info: [ 20%] LOSS: training ≈ 0.2705
[ Info: [ 20%] LOSS: training ≈ 0.27  
[ Info: [ 21%] LOSS: training ≈ 0.2695
[ Info: [ 22%] LOSS: training ≈ 0.269 
[ Info: [ 22%] LOSS: training ≈ 0.2685
[ Info: [ 22%] LOSS: training ≈ 0.2681
[ Info: [ 23%] LOSS: training ≈ 0.2677
[ Info: [ 24%] LOSS: training ≈ 0.2673
[ Info: [ 24%] LOSS: training ≈ 0.2669
[ Info: [ 24%] LOSS: training ≈ 0.2665
[ Info: [ 25%] LOSS: training ≈ 0.2661
[ Info: [ 26%] LOSS: training ≈ 0.2657
[ Info: [ 26%] LOSS: training ≈ 0.2654
[ Info: [ 26%] LOSS: training ≈ 0.265 
[ Info: [ 27%] LOSS: training ≈ 0.2647
[ Info: [ 28%] LOSS: training ≈ 0.2644
[ Info: [ 28%] LOSS: training ≈ 0.2641
[ Info: [ 28%] LOSS: training ≈ 0.2638
[ Info: [ 29%] LOSS: training ≈ 0.2635
[ Info: [ 30%] LOSS: training ≈ 0.2632
[ Info: [ 30%] LOSS: training ≈ 0.263 
[ Info: [ 30%] LOSS: training ≈ 0.2627
[ Info: [ 31%] LOSS: training ≈ 0.2625
[ Info: [ 32%] LOSS: training ≈ 0.2622
[ Info: [ 32%] LOSS: training ≈ 0.262 
[ Info: [ 32%] LOSS: training ≈ 0.2618
[ Info: [ 33%] LOSS: training ≈ 0.2615
[ Info: [ 34%] LOSS: training ≈ 0.2613
[ Info: [ 34%] LOSS: training ≈ 0.2611
[ Info: [ 34%] LOSS: training ≈ 0.2609
[ Info: [ 35%] LOSS: training ≈ 0.2607
[ Info: [ 36%] LOSS: training ≈ 0.2605
[ Info: [ 36%] LOSS: training ≈ 0.2603
[ Info: [ 36%] LOSS: training ≈ 0.2602
[ Info: [ 37%] LOSS: training ≈ 0.26  
[ Info: [ 38%] LOSS: training ≈ 0.2598
[ Info: [ 38%] LOSS: training ≈ 0.2597
[ Info: [ 38%] LOSS: training ≈ 0.2595
[ Info: [ 39%] LOSS: training ≈ 0.2593
[ Info: [ 40%] LOSS: training ≈ 0.2592
[ Info: [ 40%] LOSS: training ≈ 0.259 
[ Info: [ 40%] LOSS: training ≈ 0.2589
[ Info: [ 41%] LOSS: training ≈ 0.2588
[ Info: [ 42%] LOSS: training ≈ 0.2586
[ Info: [ 42%] LOSS: training ≈ 0.2585
[ Info: [ 42%] LOSS: training ≈ 0.2584
[ Info: [ 43%] LOSS: training ≈ 0.2582
[ Info: [ 44%] LOSS: training ≈ 0.2581
[ Info: [ 44%] LOSS: training ≈ 0.258 
[ Info: [ 44%] LOSS: training ≈ 0.2579
[ Info: [ 45%] LOSS: training ≈ 0.2578
[ Info: [ 46%] LOSS: training ≈ 0.2577
[ Info: [ 46%] LOSS: training ≈ 0.2576
[ Info: [ 46%] LOSS: training ≈ 0.2574
[ Info: [ 47%] LOSS: training ≈ 0.2573
[ Info: [ 48%] LOSS: training ≈ 0.2572
[ Info: [ 48%] LOSS: training ≈ 0.2572
[ Info: [ 48%] LOSS: training ≈ 0.2571
[ Info: [ 49%] LOSS: training ≈ 0.257 
[ Info: [ 50%] LOSS: training ≈ 0.2569
[ Info: [ 50%] LOSS: training ≈ 0.2568
[ Info: [ 50%] LOSS: training ≈ 0.2567
[ Info: [ 51%] LOSS: training ≈ 0.2566
[ Info: [ 52%] LOSS: training ≈ 0.2565
[ Info: [ 52%] LOSS: training ≈ 0.2565
[ Info: [ 52%] LOSS: training ≈ 0.2564
[ Info: [ 53%] LOSS: training ≈ 0.2563
[ Info: [ 54%] LOSS: training ≈ 0.2562
[ Info: [ 54%] LOSS: training ≈ 0.2562
[ Info: [ 55%] LOSS: training ≈ 0.2561
[ Info: [ 55%] LOSS: training ≈ 0.256 
[ Info: [ 56%] LOSS: training ≈ 0.256 
[ Info: [ 56%] LOSS: training ≈ 0.2559
[ Info: [ 56%] LOSS: training ≈ 0.2558
[ Info: [ 57%] LOSS: training ≈ 0.2558
[ Info: [ 57%] LOSS: training ≈ 0.2557
[ Info: [ 58%] LOSS: training ≈ 0.2556
[ Info: [ 58%] LOSS: training ≈ 0.2556
[ Info: [ 59%] LOSS: training ≈ 0.2555
[ Info: [ 60%] LOSS: training ≈ 0.2555
[ Info: [ 60%] LOSS: training ≈ 0.2554
[ Info: [ 60%] LOSS: training ≈ 0.2554
[ Info: [ 61%] LOSS: training ≈ 0.2553
[ Info: [ 62%] LOSS: training ≈ 0.2553
[ Info: [ 62%] LOSS: training ≈ 0.2552
[ Info: [ 62%] LOSS: training ≈ 0.2552
[ Info: [ 63%] LOSS: training ≈ 0.2551
[ Info: [ 64%] LOSS: training ≈ 0.2551
[ Info: [ 64%] LOSS: training ≈ 0.255 
[ Info: [ 64%] LOSS: training ≈ 0.255 
[ Info: [ 65%] LOSS: training ≈ 0.2549
[ Info: [ 66%] LOSS: training ≈ 0.2549
[ Info: [ 66%] LOSS: training ≈ 0.2548
[ Info: [ 66%] LOSS: training ≈ 0.2548
[ Info: [ 67%] LOSS: training ≈ 0.2548
[ Info: [ 68%] LOSS: training ≈ 0.2547
[ Info: [ 68%] LOSS: training ≈ 0.2547
[ Info: [ 68%] LOSS: training ≈ 0.2546
[ Info: [ 69%] LOSS: training ≈ 0.2546
[ Info: [ 70%] LOSS: training ≈ 0.2546
[ Info: [ 70%] LOSS: training ≈ 0.2545
[ Info: [ 70%] LOSS: training ≈ 0.2545
[ Info: [ 71%] LOSS: training ≈ 0.2545
[ Info: [ 72%] LOSS: training ≈ 0.2544
[ Info: [ 72%] LOSS: training ≈ 0.2544
[ Info: [ 72%] LOSS: training ≈ 0.2544
[ Info: [ 73%] LOSS: training ≈ 0.2543
[ Info: [ 74%] LOSS: training ≈ 0.2543
[ Info: [ 74%] LOSS: training ≈ 0.2543
[ Info: [ 74%] LOSS: training ≈ 0.2542
[ Info: [ 75%] LOSS: training ≈ 0.2542
[ Info: [ 76%] LOSS: training ≈ 0.2542
[ Info: [ 76%] LOSS: training ≈ 0.2541
[ Info: [ 76%] LOSS: training ≈ 0.2541
[ Info: [ 77%] LOSS: training ≈ 0.2541
[ Info: [ 78%] LOSS: training ≈ 0.2541
[ Info: [ 78%] LOSS: training ≈ 0.254 
[ Info: [ 78%] LOSS: training ≈ 0.254 
[ Info: [ 79%] LOSS: training ≈ 0.254 
[ Info: [ 80%] LOSS: training ≈ 0.254 
[ Info: [ 80%] LOSS: training ≈ 0.2539
[ Info: [ 80%] LOSS: training ≈ 0.2539
[ Info: [ 81%] LOSS: training ≈ 0.2539
[ Info: [ 82%] LOSS: training ≈ 0.2539
[ Info: [ 82%] LOSS: training ≈ 0.2538
[ Info: [ 82%] LOSS: training ≈ 0.2538
[ Info: [ 83%] LOSS: training ≈ 0.2538
[ Info: [ 84%] LOSS: training ≈ 0.2538
[ Info: [ 84%] LOSS: training ≈ 0.2537
[ Info: [ 84%] LOSS: training ≈ 0.2537
[ Info: [ 85%] LOSS: training ≈ 0.2537
[ Info: [ 86%] LOSS: training ≈ 0.2537
[ Info: [ 86%] LOSS: training ≈ 0.2537
[ Info: [ 86%] LOSS: training ≈ 0.2536
[ Info: [ 87%] LOSS: training ≈ 0.2536
[ Info: [ 88%] LOSS: training ≈ 0.2536
[ Info: [ 88%] LOSS: training ≈ 0.2536
[ Info: [ 88%] LOSS: training ≈ 0.2536
[ Info: [ 89%] LOSS: training ≈ 0.2535
[ Info: [ 90%] LOSS: training ≈ 0.2535
[ Info: [ 90%] LOSS: training ≈ 0.2535
[ Info: [ 90%] LOSS: training ≈ 0.2535
[ Info: [ 91%] LOSS: training ≈ 0.2535
[ Info: [ 92%] LOSS: training ≈ 0.2535
[ Info: [ 92%] LOSS: training ≈ 0.2534
[ Info: [ 92%] LOSS: training ≈ 0.2534
[ Info: [ 93%] LOSS: training ≈ 0.2534
[ Info: [ 94%] LOSS: training ≈ 0.2534
[ Info: [ 94%] LOSS: training ≈ 0.2534
[ Info: [ 94%] LOSS: training ≈ 0.2534
[ Info: [ 95%] LOSS: training ≈ 0.2533
[ Info: [ 96%] LOSS: training ≈ 0.2533
[ Info: [ 96%] LOSS: training ≈ 0.2533
[ Info: [ 96%] LOSS: training ≈ 0.2533
[ Info: [ 97%] LOSS: training ≈ 0.2533
[ Info: [ 98%] LOSS: training ≈ 0.2533
[ Info: [ 98%] LOSS: training ≈ 0.2533
[ Info: [ 98%] LOSS: training ≈ 0.2532
[ Info: [ 99%] LOSS: training ≈ 0.2532
[ Info: [100%] LOSS: training ≈ 0.2532
[ Info: [100%] LOSS: training ≈ 0.2532
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
[ Info: Baseline mcc: -2.8367742685852565e-17
[ Info: Optimal 1 variables model - mcc ≈ 0.7522
[ Info: Optimal 2 variables model - mcc ≈ 0.7609
[ Info: Optimal 3 variables model - mcc ≈ 0.7876
[ Info: Optimal 4 variables model - mcc ≈ 0.7876
[ Info: Optimal 5 variables model - mcc ≈ 0.791
[ Info: Optimal 6 variables model - mcc ≈ 0.7972
[ Info: Optimal 7 variables model - mcc ≈ 0.7987
[ Info: Optimal 8 variables model - mcc ≈ 0.8097
[ Info: Returning model with 8 variables - mcc ≈ 0.8097
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/selection.jl:90
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/selection.jl:90
[ Info: [ 2 vars.] MCC val. ≈ -0.0
[ Info: [ 3 vars.] MCC val. ≈ 0.807
[ Info: [ 4 vars.] MCC val. ≈ 0.814
[ Info: [ 5 vars.] MCC val. ≈ 0.862
[ Info: [ 6 vars.] MCC val. ≈ 0.869
[ Info: [ 7 vars.] MCC val. ≈ 0.876
[ Info: Optimal var. pool: [1, 12, 18, 3, 4, 13, 16]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/selection.jl:44
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/selection.jl:44
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/selection.jl:90
[ Info: [ 0 vars.] MCC val. ≈ -0.0
[ Info: [ 1 vars.] MCC val. ≈ 0.8
[ Info: [ 2 vars.] MCC val. ≈ 0.835
[ Info: [ 3 vars.] MCC val. ≈ 0.85
[ Info: [ 4 vars.] MCC val. ≈ 0.856
[ Info: [ 5 vars.] MCC val. ≈ 0.857
[ Info: Optimal var. pool: [8, 2, 5, 3, 6]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/selection.jl:44
[ Info: [19 vars.] MCC val. ≈ -0.0
[ Info: [18 vars.] MCC val. ≈ 0.775
[ Info: [17 vars.] MCC val. ≈ 0.789
[ Info: [16 vars.] MCC val. ≈ 0.795
[ Info: Optimal var. pool: [1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 15, 16, 18, 19]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/selection.jl:44
[ Info: [ 9 vars.] MCC val. ≈ -0.0
[ Info: [ 8 vars.] MCC val. ≈ 0.759
[ Info: [ 7 vars.] MCC val. ≈ 0.766
[ Info: Optimal var. pool: [1, 3, 5, 6, 7, 8, 9]
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/selection.jl:90
[ Info: [ 2 vars.] MCC val. ≈ -0.0
[ Info: [ 3 vars.] MCC val. ≈ 0.784
[ Info: [ 4 vars.] MCC val. ≈ 0.829
[ Info: Optimal var. pool: [12, 13, 1, 3]
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/vif.jl:24
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/xCpER/src/variables/selection.jl:90
[ Info: [ 0 vars.] MCC val. ≈ -0.0
[ Info: [ 1 vars.] MCC val. ≈ 0.723
[ Info: [ 2 vars.] MCC val. ≈ 0.774
[ Info: [ 3 vars.] MCC val. ≈ 0.851
[ Info: [ 4 vars.] MCC val. ≈ 0.858
[ Info: Optimal var. pool: [5, 7, 4, 19]
Test Summary: | Pass  Total      Time
Package       |  373    373  20m31.4s
     Testing SDeMo tests passed 

Testing completed after 1282.51s

PkgEval succeeded after 1347.01s