Package evaluation of SDeMo on Julia 1.13.0-DEV.733 (c0ecfe9bcc*) started at 2025-06-12T16:52:59.858


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

Installing PkgEval dependencies (TestEnv)...

Set-up completed after 8.17s


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

Installing SDeMo...
   Resolving package versions...
    Updating `~/.julia/environments/v1.13/Project.toml`
  [3e5feb82] + SDeMo v1.4.0
    Updating `~/.julia/environments/v1.13/Manifest.toml`
  [66dad0bd] + AliasTables v1.1.3
  [7d9fca2a] + Arpack v0.5.4
  [34da2185] + Compat v4.16.0
  [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 v1.7.0
  [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 v1.4.0
  [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 v1.12.0
  [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 v1.12.0
  [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 v8.12.1+1
  [e37daf67] + LibGit2_jll v1.9.0+0
  [29816b5a] + LibSSH2_jll v1.11.3+1
  [14a3606d] + MozillaCACerts_jll v2025.5.20
  [4536629a] + OpenBLAS_jll v0.3.29+0
  [05823500] + OpenLibm_jll v0.8.5+0
  [458c3c95] + OpenSSL_jll v3.5.0+0
  [bea87d4a] + SuiteSparse_jll v7.10.1+0
  [83775a58] + Zlib_jll v1.3.1+2
  [8e850b90] + libblastrampoline_jll v5.12.0+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 4.03s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...

Precompilation completed after 33.7s


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

     Testing SDeMo
      Status `/tmp/jl_I16GeY/Project.toml`
  [3e5feb82] SDeMo v1.4.0
  [10745b16] Statistics v1.11.1
  [f8b46487] TestItemRunner v1.1.0
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_I16GeY/Manifest.toml`
  [66dad0bd] AliasTables v1.1.3
  [7d9fca2a] Arpack v0.5.4
  [34da2185] Compat v4.16.0
  [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 v1.7.0
  [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 v1.4.0
  [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 v1.12.0
  [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 v1.12.0
  [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 v8.12.1+1
  [e37daf67] LibGit2_jll v1.9.0+0
  [29816b5a] LibSSH2_jll v1.11.3+1
  [14a3606d] MozillaCACerts_jll v2025.5.20
  [4536629a] OpenBLAS_jll v0.3.29+0
  [05823500] OpenLibm_jll v0.8.5+0
  [458c3c95] OpenSSL_jll v3.5.0+0
  [bea87d4a] SuiteSparse_jll v7.10.1+0
  [83775a58] Zlib_jll v1.3.1+2
  [8e850b90] libblastrampoline_jll v5.12.0+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...
[ Info: [  0%] LOSS: training ≈ 0.493  validation ≈ 0.5018 (102%)
[ Info: [  1%] LOSS: training ≈ 0.4176 validation ≈ 0.4423 (106%)
[ Info: [  2%] LOSS: training ≈ 0.3802 validation ≈ 0.4142 (109%)
[ Info: [  2%] LOSS: training ≈ 0.3579 validation ≈ 0.3983 (111%)
[ Info: [  2%] LOSS: training ≈ 0.3431 validation ≈ 0.3881 (113%)
[ Info: [  3%] LOSS: training ≈ 0.3324 validation ≈ 0.381  (115%)
[ Info: [  4%] LOSS: training ≈ 0.3242 validation ≈ 0.3757 (116%)
[ Info: [  4%] LOSS: training ≈ 0.3177 validation ≈ 0.3715 (117%)
[ Info: [  4%] LOSS: training ≈ 0.3124 validation ≈ 0.368  (118%)
[ Info: [  5%] LOSS: training ≈ 0.3079 validation ≈ 0.3651 (119%)
[ Info: [  6%] LOSS: training ≈ 0.304  validation ≈ 0.3625 (119%)
[ Info: [  6%] LOSS: training ≈ 0.3007 validation ≈ 0.3602 (120%)
[ Info: [  6%] LOSS: training ≈ 0.2977 validation ≈ 0.3581 (120%)
[ Info: [  7%] LOSS: training ≈ 0.295  validation ≈ 0.3562 (121%)
[ Info: [  8%] LOSS: training ≈ 0.2926 validation ≈ 0.3544 (121%)
[ Info: [  8%] LOSS: training ≈ 0.2904 validation ≈ 0.3527 (121%)
[ Info: [  8%] LOSS: training ≈ 0.2884 validation ≈ 0.3511 (122%)
[ Info: [  9%] LOSS: training ≈ 0.2865 validation ≈ 0.3496 (122%)
[ Info: [ 10%] LOSS: training ≈ 0.2848 validation ≈ 0.3482 (122%)
[ Info: [ 10%] LOSS: training ≈ 0.2832 validation ≈ 0.3469 (122%)
[ Info: [ 10%] LOSS: training ≈ 0.2817 validation ≈ 0.3456 (123%)
[ Info: [ 11%] LOSS: training ≈ 0.2803 validation ≈ 0.3444 (123%)
[ Info: [ 12%] LOSS: training ≈ 0.279  validation ≈ 0.3432 (123%)
[ Info: [ 12%] LOSS: training ≈ 0.2777 validation ≈ 0.342  (123%)
[ Info: [ 12%] LOSS: training ≈ 0.2766 validation ≈ 0.3409 (123%)
[ Info: [ 13%] LOSS: training ≈ 0.2755 validation ≈ 0.3399 (123%)
[ Info: [ 14%] LOSS: training ≈ 0.2744 validation ≈ 0.3388 (123%)
[ Info: [ 14%] LOSS: training ≈ 0.2734 validation ≈ 0.3379 (124%)
[ Info: [ 14%] LOSS: training ≈ 0.2725 validation ≈ 0.3369 (124%)
[ Info: [ 15%] LOSS: training ≈ 0.2716 validation ≈ 0.336  (124%)
[ Info: [ 16%] LOSS: training ≈ 0.2707 validation ≈ 0.3351 (124%)
[ Info: [ 16%] LOSS: training ≈ 0.2699 validation ≈ 0.3342 (124%)
[ Info: [ 16%] LOSS: training ≈ 0.2691 validation ≈ 0.3333 (124%)
[ Info: [ 17%] LOSS: training ≈ 0.2683 validation ≈ 0.3325 (124%)
[ Info: [ 18%] LOSS: training ≈ 0.2676 validation ≈ 0.3317 (124%)
[ Info: [ 18%] LOSS: training ≈ 0.2669 validation ≈ 0.3309 (124%)
[ Info: [ 18%] LOSS: training ≈ 0.2662 validation ≈ 0.3302 (124%)
[ Info: [ 19%] LOSS: training ≈ 0.2656 validation ≈ 0.3294 (124%)
[ Info: [ 20%] LOSS: training ≈ 0.265  validation ≈ 0.3287 (124%)
[ Info: [ 20%] LOSS: training ≈ 0.2644 validation ≈ 0.328  (124%)
[ Info: [ 20%] LOSS: training ≈ 0.2638 validation ≈ 0.3273 (124%)
[ Info: [ 21%] LOSS: training ≈ 0.2632 validation ≈ 0.3267 (124%)
[ Info: [ 22%] LOSS: training ≈ 0.2627 validation ≈ 0.326  (124%)
[ Info: [ 22%] LOSS: training ≈ 0.2622 validation ≈ 0.3254 (124%)
[ Info: [ 22%] LOSS: training ≈ 0.2617 validation ≈ 0.3248 (124%)
[ Info: [ 23%] LOSS: training ≈ 0.2612 validation ≈ 0.3242 (124%)
[ Info: [ 24%] LOSS: training ≈ 0.2607 validation ≈ 0.3236 (124%)
[ Info: [ 24%] LOSS: training ≈ 0.2603 validation ≈ 0.323  (124%)
[ Info: [ 24%] LOSS: training ≈ 0.2599 validation ≈ 0.3225 (124%)
[ Info: [ 25%] LOSS: training ≈ 0.2594 validation ≈ 0.3219 (124%)
[ Info: [ 26%] LOSS: training ≈ 0.259  validation ≈ 0.3214 (124%)
[ Info: [ 26%] LOSS: training ≈ 0.2586 validation ≈ 0.3209 (124%)
[ Info: [ 26%] LOSS: training ≈ 0.2583 validation ≈ 0.3204 (124%)
[ Info: [ 27%] LOSS: training ≈ 0.2579 validation ≈ 0.3199 (124%)
[ Info: [ 28%] LOSS: training ≈ 0.2575 validation ≈ 0.3195 (124%)
[ Info: [ 28%] LOSS: training ≈ 0.2572 validation ≈ 0.319  (124%)
[ Info: [ 28%] LOSS: training ≈ 0.2568 validation ≈ 0.3185 (124%)
[ Info: [ 29%] LOSS: training ≈ 0.2565 validation ≈ 0.3181 (124%)
[ Info: [ 30%] LOSS: training ≈ 0.2562 validation ≈ 0.3177 (124%)
[ Info: [ 30%] LOSS: training ≈ 0.2559 validation ≈ 0.3173 (124%)
[ Info: [ 30%] LOSS: training ≈ 0.2556 validation ≈ 0.3168 (124%)
[ Info: [ 31%] LOSS: training ≈ 0.2553 validation ≈ 0.3165 (124%)
[ Info: [ 32%] LOSS: training ≈ 0.255  validation ≈ 0.3161 (124%)
[ Info: [ 32%] LOSS: training ≈ 0.2547 validation ≈ 0.3157 (124%)
[ Info: [ 32%] LOSS: training ≈ 0.2544 validation ≈ 0.3153 (124%)
[ Info: [ 33%] LOSS: training ≈ 0.2542 validation ≈ 0.315  (124%)
[ Info: [ 34%] LOSS: training ≈ 0.2539 validation ≈ 0.3146 (124%)
[ Info: [ 34%] LOSS: training ≈ 0.2537 validation ≈ 0.3143 (124%)
[ Info: [ 34%] LOSS: training ≈ 0.2534 validation ≈ 0.3139 (124%)
[ Info: [ 35%] LOSS: training ≈ 0.2532 validation ≈ 0.3136 (124%)
[ Info: [ 36%] LOSS: training ≈ 0.253  validation ≈ 0.3133 (124%)
[ Info: [ 36%] LOSS: training ≈ 0.2528 validation ≈ 0.313  (124%)
[ Info: [ 36%] LOSS: training ≈ 0.2525 validation ≈ 0.3127 (124%)
[ Info: [ 37%] LOSS: training ≈ 0.2523 validation ≈ 0.3124 (124%)
[ Info: [ 38%] LOSS: training ≈ 0.2521 validation ≈ 0.3121 (124%)
[ Info: [ 38%] LOSS: training ≈ 0.2519 validation ≈ 0.3118 (124%)
[ Info: [ 38%] LOSS: training ≈ 0.2517 validation ≈ 0.3115 (124%)
[ Info: [ 39%] LOSS: training ≈ 0.2515 validation ≈ 0.3112 (124%)
[ Info: [ 40%] LOSS: training ≈ 0.2514 validation ≈ 0.311  (124%)
[ Info: [ 40%] LOSS: training ≈ 0.2512 validation ≈ 0.3107 (124%)
[ Info: [ 40%] LOSS: training ≈ 0.251  validation ≈ 0.3105 (124%)
[ Info: [ 41%] LOSS: training ≈ 0.2508 validation ≈ 0.3102 (124%)
[ Info: [ 42%] LOSS: training ≈ 0.2507 validation ≈ 0.31   (124%)
[ Info: [ 42%] LOSS: training ≈ 0.2505 validation ≈ 0.3097 (124%)
[ Info: [ 42%] LOSS: training ≈ 0.2503 validation ≈ 0.3095 (124%)
[ Info: [ 43%] LOSS: training ≈ 0.2502 validation ≈ 0.3093 (124%)
[ Info: [ 44%] LOSS: training ≈ 0.25   validation ≈ 0.3091 (124%)
[ Info: [ 44%] LOSS: training ≈ 0.2499 validation ≈ 0.3088 (124%)
[ Info: [ 44%] LOSS: training ≈ 0.2497 validation ≈ 0.3086 (124%)
[ Info: [ 45%] LOSS: training ≈ 0.2496 validation ≈ 0.3084 (124%)
[ Info: [ 46%] LOSS: training ≈ 0.2495 validation ≈ 0.3082 (124%)
[ Info: [ 46%] LOSS: training ≈ 0.2493 validation ≈ 0.308  (124%)
[ Info: [ 46%] LOSS: training ≈ 0.2492 validation ≈ 0.3078 (124%)
[ Info: [ 47%] LOSS: training ≈ 0.2491 validation ≈ 0.3076 (124%)
[ Info: [ 48%] LOSS: training ≈ 0.2489 validation ≈ 0.3075 (124%)
[ Info: [ 48%] LOSS: training ≈ 0.2488 validation ≈ 0.3073 (123%)
[ Info: [ 48%] LOSS: training ≈ 0.2487 validation ≈ 0.3071 (123%)
[ Info: [ 49%] LOSS: training ≈ 0.2486 validation ≈ 0.3069 (123%)
[ Info: [ 50%] LOSS: training ≈ 0.2485 validation ≈ 0.3067 (123%)
[ Info: [ 50%] LOSS: training ≈ 0.2484 validation ≈ 0.3066 (123%)
[ Info: [ 50%] LOSS: training ≈ 0.2482 validation ≈ 0.3064 (123%)
[ Info: [ 51%] LOSS: training ≈ 0.2481 validation ≈ 0.3063 (123%)
[ Info: [ 52%] LOSS: training ≈ 0.248  validation ≈ 0.3061 (123%)
[ Info: [ 52%] LOSS: training ≈ 0.2479 validation ≈ 0.3059 (123%)
[ Info: [ 52%] LOSS: training ≈ 0.2478 validation ≈ 0.3058 (123%)
[ Info: [ 53%] LOSS: training ≈ 0.2477 validation ≈ 0.3057 (123%)
[ Info: [ 54%] LOSS: training ≈ 0.2476 validation ≈ 0.3055 (123%)
[ Info: [ 54%] LOSS: training ≈ 0.2475 validation ≈ 0.3054 (123%)
[ Info: [ 55%] LOSS: training ≈ 0.2474 validation ≈ 0.3052 (123%)
[ Info: [ 55%] LOSS: training ≈ 0.2474 validation ≈ 0.3051 (123%)
[ Info: [ 56%] LOSS: training ≈ 0.2473 validation ≈ 0.305  (123%)
[ Info: [ 56%] LOSS: training ≈ 0.2472 validation ≈ 0.3048 (123%)
[ Info: [ 56%] LOSS: training ≈ 0.2471 validation ≈ 0.3047 (123%)
[ Info: [ 57%] LOSS: training ≈ 0.247  validation ≈ 0.3046 (123%)
[ Info: [ 57%] LOSS: training ≈ 0.2469 validation ≈ 0.3045 (123%)
[ Info: [ 58%] LOSS: training ≈ 0.2469 validation ≈ 0.3043 (123%)
[ Info: [ 58%] LOSS: training ≈ 0.2468 validation ≈ 0.3042 (123%)
[ Info: [ 59%] LOSS: training ≈ 0.2467 validation ≈ 0.3041 (123%)
[ Info: [ 60%] LOSS: training ≈ 0.2466 validation ≈ 0.304  (123%)
[ Info: [ 60%] LOSS: training ≈ 0.2465 validation ≈ 0.3039 (123%)
[ Info: [ 60%] LOSS: training ≈ 0.2465 validation ≈ 0.3038 (123%)
[ Info: [ 61%] LOSS: training ≈ 0.2464 validation ≈ 0.3037 (123%)
[ Info: [ 62%] LOSS: training ≈ 0.2463 validation ≈ 0.3036 (123%)
[ Info: [ 62%] LOSS: training ≈ 0.2463 validation ≈ 0.3035 (123%)
[ Info: [ 62%] LOSS: training ≈ 0.2462 validation ≈ 0.3033 (123%)
[ Info: [ 63%] LOSS: training ≈ 0.2461 validation ≈ 0.3033 (123%)
[ Info: [ 64%] LOSS: training ≈ 0.2461 validation ≈ 0.3032 (123%)
[ Info: [ 64%] LOSS: training ≈ 0.246  validation ≈ 0.3031 (123%)
[ Info: [ 64%] LOSS: training ≈ 0.2459 validation ≈ 0.303  (123%)
[ Info: [ 65%] LOSS: training ≈ 0.2459 validation ≈ 0.3029 (123%)
[ Info: [ 66%] LOSS: training ≈ 0.2458 validation ≈ 0.3028 (123%)
[ Info: [ 66%] LOSS: training ≈ 0.2458 validation ≈ 0.3027 (123%)
[ Info: [ 66%] LOSS: training ≈ 0.2457 validation ≈ 0.3026 (123%)
[ Info: [ 67%] LOSS: training ≈ 0.2457 validation ≈ 0.3025 (123%)
[ Info: [ 68%] LOSS: training ≈ 0.2456 validation ≈ 0.3024 (123%)
[ Info: [ 68%] LOSS: training ≈ 0.2455 validation ≈ 0.3024 (123%)
[ Info: [ 68%] LOSS: training ≈ 0.2455 validation ≈ 0.3023 (123%)
[ Info: [ 69%] LOSS: training ≈ 0.2454 validation ≈ 0.3022 (123%)
[ Info: [ 70%] LOSS: training ≈ 0.2454 validation ≈ 0.3021 (123%)
[ Info: [ 70%] LOSS: training ≈ 0.2453 validation ≈ 0.302  (123%)
[ Info: [ 70%] LOSS: training ≈ 0.2453 validation ≈ 0.302  (123%)
[ Info: [ 71%] LOSS: training ≈ 0.2452 validation ≈ 0.3019 (123%)
[ Info: [ 72%] LOSS: training ≈ 0.2452 validation ≈ 0.3018 (123%)
[ Info: [ 72%] LOSS: training ≈ 0.2452 validation ≈ 0.3017 (123%)
[ Info: [ 72%] LOSS: training ≈ 0.2451 validation ≈ 0.3017 (123%)
[ Info: [ 73%] LOSS: training ≈ 0.2451 validation ≈ 0.3016 (123%)
[ Info: [ 74%] LOSS: training ≈ 0.245  validation ≈ 0.3015 (123%)
[ Info: [ 74%] LOSS: training ≈ 0.245  validation ≈ 0.3015 (123%)
[ Info: [ 74%] LOSS: training ≈ 0.2449 validation ≈ 0.3014 (123%)
[ Info: [ 75%] LOSS: training ≈ 0.2449 validation ≈ 0.3013 (123%)
[ Info: [ 76%] LOSS: training ≈ 0.2449 validation ≈ 0.3013 (123%)
[ Info: [ 76%] LOSS: training ≈ 0.2448 validation ≈ 0.3012 (123%)
[ Info: [ 76%] LOSS: training ≈ 0.2448 validation ≈ 0.3012 (123%)
[ Info: [ 77%] LOSS: training ≈ 0.2447 validation ≈ 0.3011 (123%)
[ Info: [ 78%] LOSS: training ≈ 0.2447 validation ≈ 0.301  (123%)
[ Info: [ 78%] LOSS: training ≈ 0.2447 validation ≈ 0.301  (123%)
[ Info: [ 78%] LOSS: training ≈ 0.2446 validation ≈ 0.3009 (123%)
[ Info: [ 79%] LOSS: training ≈ 0.2446 validation ≈ 0.3009 (123%)
[ Info: [ 80%] LOSS: training ≈ 0.2445 validation ≈ 0.3008 (123%)
[ Info: [ 80%] LOSS: training ≈ 0.2445 validation ≈ 0.3008 (123%)
[ Info: [ 80%] LOSS: training ≈ 0.2445 validation ≈ 0.3007 (123%)
[ Info: [ 81%] LOSS: training ≈ 0.2444 validation ≈ 0.3007 (123%)
[ Info: [ 82%] LOSS: training ≈ 0.2444 validation ≈ 0.3006 (123%)
[ Info: [ 82%] LOSS: training ≈ 0.2444 validation ≈ 0.3006 (123%)
[ Info: [ 82%] LOSS: training ≈ 0.2443 validation ≈ 0.3005 (123%)
[ Info: [ 83%] LOSS: training ≈ 0.2443 validation ≈ 0.3005 (123%)
[ Info: [ 84%] LOSS: training ≈ 0.2443 validation ≈ 0.3004 (123%)
[ Info: [ 84%] LOSS: training ≈ 0.2443 validation ≈ 0.3004 (123%)
[ Info: [ 84%] LOSS: training ≈ 0.2442 validation ≈ 0.3003 (123%)
[ Info: [ 85%] LOSS: training ≈ 0.2442 validation ≈ 0.3003 (123%)
[ Info: [ 86%] LOSS: training ≈ 0.2442 validation ≈ 0.3002 (123%)
[ Info: [ 86%] LOSS: training ≈ 0.2441 validation ≈ 0.3002 (123%)
[ Info: [ 86%] LOSS: training ≈ 0.2441 validation ≈ 0.3001 (123%)
[ Info: [ 87%] LOSS: training ≈ 0.2441 validation ≈ 0.3001 (123%)
[ Info: [ 88%] LOSS: training ≈ 0.244  validation ≈ 0.3    (123%)
[ Info: [ 88%] LOSS: training ≈ 0.244  validation ≈ 0.3    (123%)
[ Info: [ 88%] LOSS: training ≈ 0.244  validation ≈ 0.3    (123%)
[ Info: [ 89%] LOSS: training ≈ 0.244  validation ≈ 0.2999 (123%)
[ Info: [ 90%] LOSS: training ≈ 0.2439 validation ≈ 0.2999 (123%)
[ Info: [ 90%] LOSS: training ≈ 0.2439 validation ≈ 0.2998 (123%)
[ Info: [ 90%] LOSS: training ≈ 0.2439 validation ≈ 0.2998 (123%)
[ Info: [ 91%] LOSS: training ≈ 0.2439 validation ≈ 0.2998 (123%)
[ Info: [ 92%] LOSS: training ≈ 0.2438 validation ≈ 0.2997 (123%)
[ Info: [ 92%] LOSS: training ≈ 0.2438 validation ≈ 0.2997 (123%)
[ Info: [ 92%] LOSS: training ≈ 0.2438 validation ≈ 0.2997 (123%)
[ Info: [ 93%] LOSS: training ≈ 0.2438 validation ≈ 0.2996 (123%)
[ Info: [ 94%] LOSS: training ≈ 0.2438 validation ≈ 0.2996 (123%)
[ Info: [ 94%] LOSS: training ≈ 0.2437 validation ≈ 0.2996 (123%)
[ Info: [ 94%] LOSS: training ≈ 0.2437 validation ≈ 0.2995 (123%)
[ Info: [ 95%] LOSS: training ≈ 0.2437 validation ≈ 0.2995 (123%)
[ Info: [ 96%] LOSS: training ≈ 0.2437 validation ≈ 0.2995 (123%)
[ Info: [ 96%] LOSS: training ≈ 0.2436 validation ≈ 0.2994 (123%)
[ Info: [ 96%] LOSS: training ≈ 0.2436 validation ≈ 0.2994 (123%)
[ Info: [ 97%] LOSS: training ≈ 0.2436 validation ≈ 0.2994 (123%)
[ Info: [ 98%] LOSS: training ≈ 0.2436 validation ≈ 0.2993 (123%)
[ Info: [ 98%] LOSS: training ≈ 0.2436 validation ≈ 0.2993 (123%)
[ Info: [ 98%] LOSS: training ≈ 0.2435 validation ≈ 0.2993 (123%)
[ Info: [ 99%] LOSS: training ≈ 0.2435 validation ≈ 0.2992 (123%)
[ Info: [100%] LOSS: training ≈ 0.2435 validation ≈ 0.2992 (123%)
[ Info: [100%] LOSS: training ≈ 0.2435 validation ≈ 0.2992 (123%)
[ 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/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:90
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:90
[ Info: [ 2 vars.] MCC val. ≈ -0.0
[ Info: [ 3 vars.] MCC val. ≈ 0.542
[ Info: Optimal var. pool: [1, 12, 17]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:44
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:44
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:90
[ Info: [ 0 vars.] MCC val. ≈ -0.0
[ Info: [ 1 vars.] MCC val. ≈ 0.746
[ Info: [ 2 vars.] MCC val. ≈ 0.766
[ Info: [ 3 vars.] MCC val. ≈ 0.78
[ Info: [ 4 vars.] MCC val. ≈ 0.787
[ Info: Optimal var. pool: [9, 3, 15, 6]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:44
[ Info: [19 vars.] MCC val. ≈ -0.0
[ Info: [18 vars.] MCC val. ≈ 0.545
[ Info: [17 vars.] MCC val. ≈ 0.758
[ Info: [16 vars.] MCC val. ≈ 0.765
[ Info: [15 vars.] MCC val. ≈ 0.772
[ Info: [14 vars.] MCC val. ≈ 0.779
[ Info: [13 vars.] MCC val. ≈ 0.786
[ Info: Optimal var. pool: [1, 2, 3, 7, 8, 9, 10, 11, 13, 15, 16, 17, 18]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:44
[ Info: [ 9 vars.] MCC val. ≈ -0.0
[ Info: [ 8 vars.] MCC val. ≈ 0.814
[ Info: [ 7 vars.] MCC val. ≈ 0.814
[ Info: Optimal var. pool: [2, 3, 5, 6, 7, 8, 9]
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:90
[ Info: [ 2 vars.] MCC val. ≈ -0.0
[ Info: [ 3 vars.] MCC val. ≈ 0.451
[ Info: Optimal var. pool: [12, 13, 1]
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:90
[ Info: [ 0 vars.] MCC val. ≈ -0.0
[ Info: [ 1 vars.] MCC val. ≈ 0.724
[ Info: [ 2 vars.] MCC val. ≈ 0.745
[ Info: Optimal var. pool: [8, 7]
[ Info: Baseline mcc: -2.8367742685852565e-17
[ Info: Optimal 1 variables model - mcc ≈ 0.7413
[ Info: Optimal 2 variables model - mcc ≈ 0.7703
[ Info: Optimal 3 variables model - mcc ≈ 0.7763
[ Info: Returning model with 4 variables - mcc ≈ 0.7763
Test Summary: | Pass  Total      Time
Package       |  297    297  25m06.5s
     Testing SDeMo tests passed 

Testing completed after 1561.72s

PkgEval succeeded after 1625.65s