Package evaluation of SDeMo on Julia 1.13.0-DEV.974 (7bbb213719*) started at 2025-08-12T16:48:45.877


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

Installing PkgEval dependencies (TestEnv)...

Set-up completed after 9.59s


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

Installing SDeMo...
   Resolving package versions...
    Updating `~/.julia/environments/v1.13/Project.toml`
  [3e5feb82] + SDeMo v1.5.1
    Updating `~/.julia/environments/v1.13/Manifest.toml`
  [66dad0bd] + AliasTables v1.1.3
  [7d9fca2a] + Arpack v0.5.4
  [9a962f9c] + DataAPI v1.16.0
  [864edb3b] + DataStructures v0.19.0
  [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 v1.5.0
  [43287f4e] + PtrArrays v1.3.0
  [1fd47b50] + QuadGK v2.11.2
  [189a3867] + Reexport v1.2.2
  [79098fc4] + Rmath v0.8.0
  [3e5feb82] + SDeMo v1.5.1
  [a2af1166] + SortingAlgorithms v1.2.2
  [276daf66] + SpecialFunctions v2.5.1
  [10745b16] + Statistics v1.11.1
  [82ae8749] + StatsAPI v1.7.1
  [2913bbd2] + StatsBase v0.34.6
  [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
  [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+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 v3.5.2+0
  [efcefdf7] + PCRE2_jll v10.45.0+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 v5.13.1+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 4.48s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...

Precompilation completed after 30.37s


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

     Testing SDeMo
      Status `/tmp/jl_mgTNdv/Project.toml`
  [3e5feb82] SDeMo v1.5.1
  [10745b16] Statistics v1.11.1
  [f8b46487] TestItemRunner v1.1.0
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_mgTNdv/Manifest.toml`
  [66dad0bd] AliasTables v1.1.3
  [7d9fca2a] Arpack v0.5.4
  [9a962f9c] DataAPI v1.16.0
  [864edb3b] DataStructures v0.19.0
  [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 v1.5.0
  [43287f4e] PtrArrays v1.3.0
  [1fd47b50] QuadGK v2.11.2
  [189a3867] Reexport v1.2.2
  [79098fc4] Rmath v0.8.0
  [3e5feb82] SDeMo v1.5.1
  [a2af1166] SortingAlgorithms v1.2.2
  [276daf66] SpecialFunctions v2.5.1
  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.7.1
  [2913bbd2] StatsBase v0.34.6
  [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+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 v3.5.2+0
  [efcefdf7] PCRE2_jll v10.45.0+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 v5.13.1+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: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/selection.jl:90
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/selection.jl:90
[ Info: [ 2 vars.] MCC val. ≈ -0.0
[ Info: [ 3 vars.] MCC val. ≈ 0.445
[ Info: Optimal var. pool: [1, 12, 2]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/selection.jl:44
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/selection.jl:44
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/selection.jl:90
[ Info: [ 0 vars.] MCC val. ≈ -0.0
[ Info: [ 1 vars.] MCC val. ≈ 0.789
[ Info: [ 2 vars.] MCC val. ≈ 0.824
[ Info: Optimal var. pool: [8, 7]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/selection.jl:44
[ Info: [19 vars.] MCC val. ≈ -0.0
[ Info: [18 vars.] MCC val. ≈ 0.529
[ Info: [17 vars.] MCC val. ≈ 0.829
[ Info: [16 vars.] MCC val. ≈ 0.842
[ Info: Optimal var. pool: [2, 3, 4, 5, 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/JWEc2/src/variables/selection.jl:44
[ Info: [ 9 vars.] MCC val. ≈ -0.0
[ Info: [ 8 vars.] MCC val. ≈ 0.828
[ Info: Optimal var. pool: [1, 2, 3, 5, 6, 7, 8, 9]
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/selection.jl:90
[ Info: [ 2 vars.] MCC val. ≈ -0.0
[ Info: [ 3 vars.] MCC val. ≈ 0.521
[ Info: Optimal var. pool: [12, 13, 1]
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/selection.jl:90
[ Info: [ 0 vars.] MCC val. ≈ -0.0
[ Info: [ 1 vars.] MCC val. ≈ 0.786
[ Info: [ 2 vars.] MCC val. ≈ 0.8
[ Info: Optimal var. pool: [8, 7]
[ Info: [  0%] LOSS: training ≈ 0.4986 validation ≈ 0.4896 ( 98%)
[ Info: [  1%] LOSS: training ≈ 0.4252 validation ≈ 0.4223 ( 99%)
[ Info: [  2%] LOSS: training ≈ 0.3892 validation ≈ 0.3881 (100%)
[ Info: [  2%] LOSS: training ≈ 0.3678 validation ≈ 0.3674 (100%)
[ Info: [  2%] LOSS: training ≈ 0.3536 validation ≈ 0.3534 (100%)
[ Info: [  3%] LOSS: training ≈ 0.3433 validation ≈ 0.3432 (100%)
[ Info: [  4%] LOSS: training ≈ 0.3355 validation ≈ 0.3353 (100%)
[ Info: [  4%] LOSS: training ≈ 0.3292 validation ≈ 0.3289 (100%)
[ Info: [  4%] LOSS: training ≈ 0.324  validation ≈ 0.3237 (100%)
[ Info: [  5%] LOSS: training ≈ 0.3197 validation ≈ 0.3192 (100%)
[ Info: [  6%] LOSS: training ≈ 0.3159 validation ≈ 0.3154 (100%)
[ Info: [  6%] LOSS: training ≈ 0.3126 validation ≈ 0.312  (100%)
[ Info: [  6%] LOSS: training ≈ 0.3096 validation ≈ 0.309  (100%)
[ Info: [  7%] LOSS: training ≈ 0.307  validation ≈ 0.3063 (100%)
[ Info: [  8%] LOSS: training ≈ 0.3045 validation ≈ 0.3038 (100%)
[ Info: [  8%] LOSS: training ≈ 0.3023 validation ≈ 0.3016 (100%)
[ Info: [  8%] LOSS: training ≈ 0.3003 validation ≈ 0.2996 (100%)
[ Info: [  9%] LOSS: training ≈ 0.2984 validation ≈ 0.2977 (100%)
[ Info: [ 10%] LOSS: training ≈ 0.2967 validation ≈ 0.2959 (100%)
[ Info: [ 10%] LOSS: training ≈ 0.2951 validation ≈ 0.2943 (100%)
[ Info: [ 10%] LOSS: training ≈ 0.2935 validation ≈ 0.2928 (100%)
[ Info: [ 11%] LOSS: training ≈ 0.2921 validation ≈ 0.2914 (100%)
[ Info: [ 12%] LOSS: training ≈ 0.2907 validation ≈ 0.2901 (100%)
[ Info: [ 12%] LOSS: training ≈ 0.2895 validation ≈ 0.2888 (100%)
[ Info: [ 12%] LOSS: training ≈ 0.2882 validation ≈ 0.2877 (100%)
[ Info: [ 13%] LOSS: training ≈ 0.2871 validation ≈ 0.2865 (100%)
[ Info: [ 14%] LOSS: training ≈ 0.286  validation ≈ 0.2855 (100%)
[ Info: [ 14%] LOSS: training ≈ 0.285  validation ≈ 0.2845 (100%)
[ Info: [ 14%] LOSS: training ≈ 0.284  validation ≈ 0.2836 (100%)
[ Info: [ 15%] LOSS: training ≈ 0.283  validation ≈ 0.2827 (100%)
[ Info: [ 16%] LOSS: training ≈ 0.2821 validation ≈ 0.2818 (100%)
[ Info: [ 16%] LOSS: training ≈ 0.2812 validation ≈ 0.281  (100%)
[ Info: [ 16%] LOSS: training ≈ 0.2804 validation ≈ 0.2802 (100%)
[ Info: [ 17%] LOSS: training ≈ 0.2796 validation ≈ 0.2795 (100%)
[ Info: [ 18%] LOSS: training ≈ 0.2788 validation ≈ 0.2788 (100%)
[ Info: [ 18%] LOSS: training ≈ 0.2781 validation ≈ 0.2781 (100%)
[ Info: [ 18%] LOSS: training ≈ 0.2774 validation ≈ 0.2774 (100%)
[ Info: [ 19%] LOSS: training ≈ 0.2767 validation ≈ 0.2768 (100%)
[ Info: [ 20%] LOSS: training ≈ 0.276  validation ≈ 0.2762 (100%)
[ Info: [ 20%] LOSS: training ≈ 0.2754 validation ≈ 0.2756 (100%)
[ Info: [ 20%] LOSS: training ≈ 0.2748 validation ≈ 0.2751 (100%)
[ Info: [ 21%] LOSS: training ≈ 0.2742 validation ≈ 0.2746 (100%)
[ Info: [ 22%] LOSS: training ≈ 0.2736 validation ≈ 0.2741 (100%)
[ Info: [ 22%] LOSS: training ≈ 0.2731 validation ≈ 0.2736 (100%)
[ Info: [ 22%] LOSS: training ≈ 0.2725 validation ≈ 0.2731 (100%)
[ Info: [ 23%] LOSS: training ≈ 0.272  validation ≈ 0.2726 (100%)
[ Info: [ 24%] LOSS: training ≈ 0.2715 validation ≈ 0.2722 (100%)
[ Info: [ 24%] LOSS: training ≈ 0.2711 validation ≈ 0.2718 (100%)
[ Info: [ 24%] LOSS: training ≈ 0.2706 validation ≈ 0.2714 (100%)
[ Info: [ 25%] LOSS: training ≈ 0.2701 validation ≈ 0.271  (100%)
[ Info: [ 26%] LOSS: training ≈ 0.2697 validation ≈ 0.2706 (100%)
[ Info: [ 26%] LOSS: training ≈ 0.2693 validation ≈ 0.2702 (100%)
[ Info: [ 26%] LOSS: training ≈ 0.2689 validation ≈ 0.2699 (100%)
[ Info: [ 27%] LOSS: training ≈ 0.2685 validation ≈ 0.2695 (100%)
[ Info: [ 28%] LOSS: training ≈ 0.2681 validation ≈ 0.2692 (100%)
[ Info: [ 28%] LOSS: training ≈ 0.2677 validation ≈ 0.2689 (100%)
[ Info: [ 28%] LOSS: training ≈ 0.2674 validation ≈ 0.2686 (100%)
[ Info: [ 29%] LOSS: training ≈ 0.267  validation ≈ 0.2683 (100%)
[ Info: [ 30%] LOSS: training ≈ 0.2667 validation ≈ 0.268  (100%)
[ Info: [ 30%] LOSS: training ≈ 0.2663 validation ≈ 0.2677 (101%)
[ Info: [ 30%] LOSS: training ≈ 0.266  validation ≈ 0.2674 (101%)
[ Info: [ 31%] LOSS: training ≈ 0.2657 validation ≈ 0.2671 (101%)
[ Info: [ 32%] LOSS: training ≈ 0.2654 validation ≈ 0.2669 (101%)
[ Info: [ 32%] LOSS: training ≈ 0.2651 validation ≈ 0.2666 (101%)
[ Info: [ 32%] LOSS: training ≈ 0.2648 validation ≈ 0.2664 (101%)
[ Info: [ 33%] LOSS: training ≈ 0.2645 validation ≈ 0.2662 (101%)
[ Info: [ 34%] LOSS: training ≈ 0.2643 validation ≈ 0.2659 (101%)
[ Info: [ 34%] LOSS: training ≈ 0.264  validation ≈ 0.2657 (101%)
[ Info: [ 34%] LOSS: training ≈ 0.2637 validation ≈ 0.2655 (101%)
[ Info: [ 35%] LOSS: training ≈ 0.2635 validation ≈ 0.2653 (101%)
[ Info: [ 36%] LOSS: training ≈ 0.2633 validation ≈ 0.2651 (101%)
[ Info: [ 36%] LOSS: training ≈ 0.263  validation ≈ 0.2649 (101%)
[ Info: [ 36%] LOSS: training ≈ 0.2628 validation ≈ 0.2647 (101%)
[ Info: [ 37%] LOSS: training ≈ 0.2626 validation ≈ 0.2645 (101%)
[ Info: [ 38%] LOSS: training ≈ 0.2623 validation ≈ 0.2643 (101%)
[ Info: [ 38%] LOSS: training ≈ 0.2621 validation ≈ 0.2642 (101%)
[ Info: [ 38%] LOSS: training ≈ 0.2619 validation ≈ 0.264  (101%)
[ Info: [ 39%] LOSS: training ≈ 0.2617 validation ≈ 0.2638 (101%)
[ Info: [ 40%] LOSS: training ≈ 0.2615 validation ≈ 0.2637 (101%)
[ Info: [ 40%] LOSS: training ≈ 0.2613 validation ≈ 0.2635 (101%)
[ Info: [ 40%] LOSS: training ≈ 0.2612 validation ≈ 0.2634 (101%)
[ Info: [ 41%] LOSS: training ≈ 0.261  validation ≈ 0.2632 (101%)
[ Info: [ 42%] LOSS: training ≈ 0.2608 validation ≈ 0.2631 (101%)
[ Info: [ 42%] LOSS: training ≈ 0.2606 validation ≈ 0.2629 (101%)
[ Info: [ 42%] LOSS: training ≈ 0.2605 validation ≈ 0.2628 (101%)
[ Info: [ 43%] LOSS: training ≈ 0.2603 validation ≈ 0.2627 (101%)
[ Info: [ 44%] LOSS: training ≈ 0.2601 validation ≈ 0.2625 (101%)
[ Info: [ 44%] LOSS: training ≈ 0.26   validation ≈ 0.2624 (101%)
[ Info: [ 44%] LOSS: training ≈ 0.2598 validation ≈ 0.2623 (101%)
[ Info: [ 45%] LOSS: training ≈ 0.2597 validation ≈ 0.2622 (101%)
[ Info: [ 46%] LOSS: training ≈ 0.2595 validation ≈ 0.2621 (101%)
[ Info: [ 46%] LOSS: training ≈ 0.2594 validation ≈ 0.2619 (101%)
[ Info: [ 46%] LOSS: training ≈ 0.2592 validation ≈ 0.2618 (101%)
[ Info: [ 47%] LOSS: training ≈ 0.2591 validation ≈ 0.2617 (101%)
[ Info: [ 48%] LOSS: training ≈ 0.259  validation ≈ 0.2616 (101%)
[ Info: [ 48%] LOSS: training ≈ 0.2588 validation ≈ 0.2615 (101%)
[ Info: [ 48%] LOSS: training ≈ 0.2587 validation ≈ 0.2614 (101%)
[ Info: [ 49%] LOSS: training ≈ 0.2586 validation ≈ 0.2613 (101%)
[ Info: [ 50%] LOSS: training ≈ 0.2585 validation ≈ 0.2612 (101%)
[ Info: [ 50%] LOSS: training ≈ 0.2584 validation ≈ 0.2611 (101%)
[ Info: [ 50%] LOSS: training ≈ 0.2582 validation ≈ 0.261  (101%)
[ Info: [ 51%] LOSS: training ≈ 0.2581 validation ≈ 0.261  (101%)
[ Info: [ 52%] LOSS: training ≈ 0.258  validation ≈ 0.2609 (101%)
[ Info: [ 52%] LOSS: training ≈ 0.2579 validation ≈ 0.2608 (101%)
[ Info: [ 52%] LOSS: training ≈ 0.2578 validation ≈ 0.2607 (101%)
[ Info: [ 53%] LOSS: training ≈ 0.2577 validation ≈ 0.2606 (101%)
[ Info: [ 54%] LOSS: training ≈ 0.2576 validation ≈ 0.2606 (101%)
[ Info: [ 54%] LOSS: training ≈ 0.2575 validation ≈ 0.2605 (101%)
[ Info: [ 55%] LOSS: training ≈ 0.2574 validation ≈ 0.2604 (101%)
[ Info: [ 55%] LOSS: training ≈ 0.2573 validation ≈ 0.2603 (101%)
[ Info: [ 56%] LOSS: training ≈ 0.2572 validation ≈ 0.2603 (101%)
[ Info: [ 56%] LOSS: training ≈ 0.2571 validation ≈ 0.2602 (101%)
[ Info: [ 56%] LOSS: training ≈ 0.257  validation ≈ 0.2601 (101%)
[ Info: [ 57%] LOSS: training ≈ 0.2569 validation ≈ 0.2601 (101%)
[ Info: [ 57%] LOSS: training ≈ 0.2569 validation ≈ 0.26   (101%)
[ Info: [ 58%] LOSS: training ≈ 0.2568 validation ≈ 0.2599 (101%)
[ Info: [ 58%] LOSS: training ≈ 0.2567 validation ≈ 0.2599 (101%)
[ Info: [ 59%] LOSS: training ≈ 0.2566 validation ≈ 0.2598 (101%)
[ Info: [ 60%] LOSS: training ≈ 0.2565 validation ≈ 0.2598 (101%)
[ Info: [ 60%] LOSS: training ≈ 0.2565 validation ≈ 0.2597 (101%)
[ Info: [ 60%] LOSS: training ≈ 0.2564 validation ≈ 0.2596 (101%)
[ Info: [ 61%] LOSS: training ≈ 0.2563 validation ≈ 0.2596 (101%)
[ Info: [ 62%] LOSS: training ≈ 0.2562 validation ≈ 0.2595 (101%)
[ Info: [ 62%] LOSS: training ≈ 0.2562 validation ≈ 0.2595 (101%)
[ Info: [ 62%] LOSS: training ≈ 0.2561 validation ≈ 0.2594 (101%)
[ Info: [ 63%] LOSS: training ≈ 0.256  validation ≈ 0.2594 (101%)
[ Info: [ 64%] LOSS: training ≈ 0.256  validation ≈ 0.2593 (101%)
[ Info: [ 64%] LOSS: training ≈ 0.2559 validation ≈ 0.2593 (101%)
[ Info: [ 64%] LOSS: training ≈ 0.2558 validation ≈ 0.2592 (101%)
[ Info: [ 65%] LOSS: training ≈ 0.2558 validation ≈ 0.2592 (101%)
[ Info: [ 66%] LOSS: training ≈ 0.2557 validation ≈ 0.2592 (101%)
[ Info: [ 66%] LOSS: training ≈ 0.2556 validation ≈ 0.2591 (101%)
[ Info: [ 66%] LOSS: training ≈ 0.2556 validation ≈ 0.2591 (101%)
[ Info: [ 67%] LOSS: training ≈ 0.2555 validation ≈ 0.259  (101%)
[ Info: [ 68%] LOSS: training ≈ 0.2555 validation ≈ 0.259  (101%)
[ Info: [ 68%] LOSS: training ≈ 0.2554 validation ≈ 0.259  (101%)
[ Info: [ 68%] LOSS: training ≈ 0.2553 validation ≈ 0.2589 (101%)
[ Info: [ 69%] LOSS: training ≈ 0.2553 validation ≈ 0.2589 (101%)
[ Info: [ 70%] LOSS: training ≈ 0.2552 validation ≈ 0.2588 (101%)
[ Info: [ 70%] LOSS: training ≈ 0.2552 validation ≈ 0.2588 (101%)
[ Info: [ 70%] LOSS: training ≈ 0.2551 validation ≈ 0.2588 (101%)
[ Info: [ 71%] LOSS: training ≈ 0.2551 validation ≈ 0.2587 (101%)
[ Info: [ 72%] LOSS: training ≈ 0.255  validation ≈ 0.2587 (101%)
[ Info: [ 72%] LOSS: training ≈ 0.255  validation ≈ 0.2587 (101%)
[ Info: [ 72%] LOSS: training ≈ 0.2549 validation ≈ 0.2586 (101%)
[ Info: [ 73%] LOSS: training ≈ 0.2549 validation ≈ 0.2586 (101%)
[ Info: [ 74%] LOSS: training ≈ 0.2548 validation ≈ 0.2586 (101%)
[ Info: [ 74%] LOSS: training ≈ 0.2548 validation ≈ 0.2586 (101%)
[ Info: [ 74%] LOSS: training ≈ 0.2547 validation ≈ 0.2585 (101%)
[ Info: [ 75%] LOSS: training ≈ 0.2547 validation ≈ 0.2585 (101%)
[ Info: [ 76%] LOSS: training ≈ 0.2547 validation ≈ 0.2585 (101%)
[ Info: [ 76%] LOSS: training ≈ 0.2546 validation ≈ 0.2584 (102%)
[ Info: [ 76%] LOSS: training ≈ 0.2546 validation ≈ 0.2584 (102%)
[ Info: [ 77%] LOSS: training ≈ 0.2545 validation ≈ 0.2584 (102%)
[ Info: [ 78%] LOSS: training ≈ 0.2545 validation ≈ 0.2584 (102%)
[ Info: [ 78%] LOSS: training ≈ 0.2545 validation ≈ 0.2583 (102%)
[ Info: [ 78%] LOSS: training ≈ 0.2544 validation ≈ 0.2583 (102%)
[ Info: [ 79%] LOSS: training ≈ 0.2544 validation ≈ 0.2583 (102%)
[ Info: [ 80%] LOSS: training ≈ 0.2543 validation ≈ 0.2583 (102%)
[ Info: [ 80%] LOSS: training ≈ 0.2543 validation ≈ 0.2583 (102%)
[ Info: [ 80%] LOSS: training ≈ 0.2543 validation ≈ 0.2582 (102%)
[ Info: [ 81%] LOSS: training ≈ 0.2542 validation ≈ 0.2582 (102%)
[ Info: [ 82%] LOSS: training ≈ 0.2542 validation ≈ 0.2582 (102%)
[ Info: [ 82%] LOSS: training ≈ 0.2542 validation ≈ 0.2582 (102%)
[ Info: [ 82%] LOSS: training ≈ 0.2541 validation ≈ 0.2581 (102%)
[ Info: [ 83%] LOSS: training ≈ 0.2541 validation ≈ 0.2581 (102%)
[ Info: [ 84%] LOSS: training ≈ 0.2541 validation ≈ 0.2581 (102%)
[ Info: [ 84%] LOSS: training ≈ 0.254  validation ≈ 0.2581 (102%)
[ Info: [ 84%] LOSS: training ≈ 0.254  validation ≈ 0.2581 (102%)
[ Info: [ 85%] LOSS: training ≈ 0.254  validation ≈ 0.2581 (102%)
[ Info: [ 86%] LOSS: training ≈ 0.2539 validation ≈ 0.258  (102%)
[ Info: [ 86%] LOSS: training ≈ 0.2539 validation ≈ 0.258  (102%)
[ Info: [ 86%] LOSS: training ≈ 0.2539 validation ≈ 0.258  (102%)
[ Info: [ 87%] LOSS: training ≈ 0.2538 validation ≈ 0.258  (102%)
[ Info: [ 88%] LOSS: training ≈ 0.2538 validation ≈ 0.258  (102%)
[ Info: [ 88%] LOSS: training ≈ 0.2538 validation ≈ 0.258  (102%)
[ Info: [ 88%] LOSS: training ≈ 0.2537 validation ≈ 0.2579 (102%)
[ Info: [ 89%] LOSS: training ≈ 0.2537 validation ≈ 0.2579 (102%)
[ Info: [ 90%] LOSS: training ≈ 0.2537 validation ≈ 0.2579 (102%)
[ Info: [ 90%] LOSS: training ≈ 0.2537 validation ≈ 0.2579 (102%)
[ Info: [ 90%] LOSS: training ≈ 0.2536 validation ≈ 0.2579 (102%)
[ Info: [ 91%] LOSS: training ≈ 0.2536 validation ≈ 0.2579 (102%)
[ Info: [ 92%] LOSS: training ≈ 0.2536 validation ≈ 0.2579 (102%)
[ Info: [ 92%] LOSS: training ≈ 0.2536 validation ≈ 0.2578 (102%)
[ Info: [ 92%] LOSS: training ≈ 0.2535 validation ≈ 0.2578 (102%)
[ Info: [ 93%] LOSS: training ≈ 0.2535 validation ≈ 0.2578 (102%)
[ Info: [ 94%] LOSS: training ≈ 0.2535 validation ≈ 0.2578 (102%)
[ Info: [ 94%] LOSS: training ≈ 0.2535 validation ≈ 0.2578 (102%)
[ Info: [ 94%] LOSS: training ≈ 0.2534 validation ≈ 0.2578 (102%)
[ Info: [ 95%] LOSS: training ≈ 0.2534 validation ≈ 0.2578 (102%)
[ Info: [ 96%] LOSS: training ≈ 0.2534 validation ≈ 0.2578 (102%)
[ Info: [ 96%] LOSS: training ≈ 0.2534 validation ≈ 0.2578 (102%)
[ Info: [ 96%] LOSS: training ≈ 0.2533 validation ≈ 0.2577 (102%)
[ Info: [ 97%] LOSS: training ≈ 0.2533 validation ≈ 0.2577 (102%)
[ Info: [ 98%] LOSS: training ≈ 0.2533 validation ≈ 0.2577 (102%)
[ Info: [ 98%] LOSS: training ≈ 0.2533 validation ≈ 0.2577 (102%)
[ Info: [ 98%] LOSS: training ≈ 0.2533 validation ≈ 0.2577 (102%)
[ Info: [ 99%] LOSS: training ≈ 0.2532 validation ≈ 0.2577 (102%)
[ Info: [100%] LOSS: training ≈ 0.2532 validation ≈ 0.2577 (102%)
[ Info: [100%] LOSS: training ≈ 0.2532 validation ≈ 0.2577 (102%)
[ 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: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/JWEc2/src/variables/vif.jl:24
[ Info: Baseline mcc: -2.8367742685852565e-17
[ Info: Optimal 1 variables model - mcc ≈ 0.7312
[ Info: Optimal 2 variables model - mcc ≈ 0.7711
[ Info: Optimal 3 variables model - mcc ≈ 0.7741
[ Info: Optimal 4 variables model - mcc ≈ 0.7791
[ Info: Optimal 5 variables model - mcc ≈ 0.78
[ Info: Optimal 6 variables model - mcc ≈ 0.8041
[ Info: Optimal 7 variables model - mcc ≈ 0.8059
[ Info: Returning model with 7 variables - mcc ≈ 0.8059
Test Summary: | Pass  Total      Time
Package       |  300    300  17m55.8s
     Testing SDeMo tests passed 

Testing completed after 1130.58s

PkgEval succeeded after 1186.94s