Package evaluation to test SDeMo on Julia 1.14.0-DEV.1589 (2d9a3f8a61*) started at 2026-01-21T09:24:48.945


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

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

Set-up completed after 10.46s


################################################################################
# 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 v2.6.1
  [10745b16] + Statistics v1.11.1
  [82ae8749] + StatsAPI v1.8.0
  [2913bbd2] + StatsBase v0.34.10
  [4c63d2b9] + StatsFuns v1.5.2
  [ec057cc2] + StructUtils v2.6.2
  [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 v0.3.29+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 5.12s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...
Precompiling packages...
  11911.6 ms  ✓ Distributions
   4551.6 ms  ✓ Distributions → DistributionsTestExt
   4527.4 ms  ✓ MultivariateStats
   5501.2 ms  ✓ SDeMo
  4 dependencies successfully precompiled in 29 seconds. 72 already precompiled.

Precompilation completed after 48.62s


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

     Testing SDeMo
      Status `/tmp/jl_oPlXRs/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_oPlXRs/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 v2.6.1
  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.8.0
  [2913bbd2] StatsBase v0.34.10
  [4c63d2b9] StatsFuns v1.5.2
  [ec057cc2] StructUtils v2.6.2
  [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 v0.3.29+0
  [05823500] OpenLibm_jll v0.8.7+0
  [458c3c95] OpenSSL_jll v3.5.4+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 ≈ 0.4941 validation ≈ 0.5027 (102%)
[ Info: [  1%] LOSS: training ≈ 0.4182 validation ≈ 0.4399 (105%)
[ Info: [  2%] LOSS: training ≈ 0.3807 validation ≈ 0.4096 (108%)
[ Info: [  2%] LOSS: training ≈ 0.3581 validation ≈ 0.3921 (109%)
[ Info: [  2%] LOSS: training ≈ 0.343  validation ≈ 0.3809 (111%)
[ Info: [  3%] LOSS: training ≈ 0.332  validation ≈ 0.3732 (112%)
[ Info: [  4%] LOSS: training ≈ 0.3236 validation ≈ 0.3675 (114%)
[ Info: [  4%] LOSS: training ≈ 0.3169 validation ≈ 0.3633 (115%)
[ Info: [  4%] LOSS: training ≈ 0.3114 validation ≈ 0.3599 (116%)
[ Info: [  5%] LOSS: training ≈ 0.3068 validation ≈ 0.3571 (116%)
[ Info: [  6%] LOSS: training ≈ 0.3029 validation ≈ 0.3548 (117%)
[ Info: [  6%] LOSS: training ≈ 0.2994 validation ≈ 0.3529 (118%)
[ Info: [  6%] LOSS: training ≈ 0.2964 validation ≈ 0.3512 (118%)
[ Info: [  7%] LOSS: training ≈ 0.2937 validation ≈ 0.3498 (119%)
[ Info: [  8%] LOSS: training ≈ 0.2913 validation ≈ 0.3484 (120%)
[ Info: [  8%] LOSS: training ≈ 0.2891 validation ≈ 0.3473 (120%)
[ Info: [  8%] LOSS: training ≈ 0.2871 validation ≈ 0.3462 (121%)
[ Info: [  9%] LOSS: training ≈ 0.2853 validation ≈ 0.3452 (121%)
[ Info: [ 10%] LOSS: training ≈ 0.2837 validation ≈ 0.3442 (121%)
[ Info: [ 10%] LOSS: training ≈ 0.2821 validation ≈ 0.3434 (122%)
[ Info: [ 10%] LOSS: training ≈ 0.2807 validation ≈ 0.3425 (122%)
[ Info: [ 11%] LOSS: training ≈ 0.2793 validation ≈ 0.3417 (122%)
[ Info: [ 12%] LOSS: training ≈ 0.2781 validation ≈ 0.341  (123%)
[ Info: [ 12%] LOSS: training ≈ 0.2769 validation ≈ 0.3403 (123%)
[ Info: [ 12%] LOSS: training ≈ 0.2758 validation ≈ 0.3396 (123%)
[ Info: [ 13%] LOSS: training ≈ 0.2747 validation ≈ 0.3389 (123%)
[ Info: [ 14%] LOSS: training ≈ 0.2737 validation ≈ 0.3383 (124%)
[ Info: [ 14%] LOSS: training ≈ 0.2728 validation ≈ 0.3376 (124%)
[ Info: [ 14%] LOSS: training ≈ 0.2719 validation ≈ 0.337  (124%)
[ Info: [ 15%] LOSS: training ≈ 0.271  validation ≈ 0.3364 (124%)
[ Info: [ 16%] LOSS: training ≈ 0.2702 validation ≈ 0.3358 (124%)
[ Info: [ 16%] LOSS: training ≈ 0.2694 validation ≈ 0.3352 (124%)
[ Info: [ 16%] LOSS: training ≈ 0.2687 validation ≈ 0.3347 (125%)
[ Info: [ 17%] LOSS: training ≈ 0.268  validation ≈ 0.3341 (125%)
[ Info: [ 18%] LOSS: training ≈ 0.2673 validation ≈ 0.3336 (125%)
[ Info: [ 18%] LOSS: training ≈ 0.2667 validation ≈ 0.3331 (125%)
[ Info: [ 18%] LOSS: training ≈ 0.266  validation ≈ 0.3325 (125%)
[ Info: [ 19%] LOSS: training ≈ 0.2654 validation ≈ 0.332  (125%)
[ Info: [ 20%] LOSS: training ≈ 0.2648 validation ≈ 0.3315 (125%)
[ Info: [ 20%] LOSS: training ≈ 0.2643 validation ≈ 0.331  (125%)
[ Info: [ 20%] LOSS: training ≈ 0.2637 validation ≈ 0.3305 (125%)
[ Info: [ 21%] LOSS: training ≈ 0.2632 validation ≈ 0.33   (125%)
[ Info: [ 22%] LOSS: training ≈ 0.2627 validation ≈ 0.3296 (125%)
[ Info: [ 22%] LOSS: training ≈ 0.2622 validation ≈ 0.3291 (126%)
[ Info: [ 22%] LOSS: training ≈ 0.2618 validation ≈ 0.3286 (126%)
[ Info: [ 23%] LOSS: training ≈ 0.2613 validation ≈ 0.3282 (126%)
[ Info: [ 24%] LOSS: training ≈ 0.2609 validation ≈ 0.3277 (126%)
[ Info: [ 24%] LOSS: training ≈ 0.2604 validation ≈ 0.3273 (126%)
[ Info: [ 24%] LOSS: training ≈ 0.26   validation ≈ 0.3269 (126%)
[ Info: [ 25%] LOSS: training ≈ 0.2596 validation ≈ 0.3265 (126%)
[ Info: [ 26%] LOSS: training ≈ 0.2592 validation ≈ 0.326  (126%)
[ Info: [ 26%] LOSS: training ≈ 0.2588 validation ≈ 0.3256 (126%)
[ Info: [ 26%] LOSS: training ≈ 0.2585 validation ≈ 0.3252 (126%)
[ Info: [ 27%] LOSS: training ≈ 0.2581 validation ≈ 0.3248 (126%)
[ Info: [ 28%] LOSS: training ≈ 0.2578 validation ≈ 0.3245 (126%)
[ Info: [ 28%] LOSS: training ≈ 0.2574 validation ≈ 0.3241 (126%)
[ Info: [ 28%] LOSS: training ≈ 0.2571 validation ≈ 0.3237 (126%)
[ Info: [ 29%] LOSS: training ≈ 0.2568 validation ≈ 0.3233 (126%)
[ Info: [ 30%] LOSS: training ≈ 0.2565 validation ≈ 0.323  (126%)
[ Info: [ 30%] LOSS: training ≈ 0.2562 validation ≈ 0.3226 (126%)
[ Info: [ 30%] LOSS: training ≈ 0.2559 validation ≈ 0.3223 (126%)
[ Info: [ 31%] LOSS: training ≈ 0.2556 validation ≈ 0.3219 (126%)
[ Info: [ 32%] LOSS: training ≈ 0.2553 validation ≈ 0.3216 (126%)
[ Info: [ 32%] LOSS: training ≈ 0.2551 validation ≈ 0.3212 (126%)
[ Info: [ 32%] LOSS: training ≈ 0.2548 validation ≈ 0.3209 (126%)
[ Info: [ 33%] LOSS: training ≈ 0.2546 validation ≈ 0.3206 (126%)
[ Info: [ 34%] LOSS: training ≈ 0.2543 validation ≈ 0.3203 (126%)
[ Info: [ 34%] LOSS: training ≈ 0.2541 validation ≈ 0.32   (126%)
[ Info: [ 34%] LOSS: training ≈ 0.2538 validation ≈ 0.3197 (126%)
[ Info: [ 35%] LOSS: training ≈ 0.2536 validation ≈ 0.3194 (126%)
[ Info: [ 36%] LOSS: training ≈ 0.2534 validation ≈ 0.3191 (126%)
[ Info: [ 36%] LOSS: training ≈ 0.2532 validation ≈ 0.3188 (126%)
[ Info: [ 36%] LOSS: training ≈ 0.2529 validation ≈ 0.3185 (126%)
[ Info: [ 37%] LOSS: training ≈ 0.2527 validation ≈ 0.3182 (126%)
[ Info: [ 38%] LOSS: training ≈ 0.2525 validation ≈ 0.318  (126%)
[ Info: [ 38%] LOSS: training ≈ 0.2523 validation ≈ 0.3177 (126%)
[ Info: [ 38%] LOSS: training ≈ 0.2521 validation ≈ 0.3175 (126%)
[ Info: [ 39%] LOSS: training ≈ 0.2519 validation ≈ 0.3172 (126%)
[ Info: [ 40%] LOSS: training ≈ 0.2518 validation ≈ 0.317  (126%)
[ Info: [ 40%] LOSS: training ≈ 0.2516 validation ≈ 0.3167 (126%)
[ Info: [ 40%] LOSS: training ≈ 0.2514 validation ≈ 0.3165 (126%)
[ Info: [ 41%] LOSS: training ≈ 0.2512 validation ≈ 0.3162 (126%)
[ Info: [ 42%] LOSS: training ≈ 0.2511 validation ≈ 0.316  (126%)
[ Info: [ 42%] LOSS: training ≈ 0.2509 validation ≈ 0.3158 (126%)
[ Info: [ 42%] LOSS: training ≈ 0.2507 validation ≈ 0.3156 (126%)
[ Info: [ 43%] LOSS: training ≈ 0.2506 validation ≈ 0.3153 (126%)
[ Info: [ 44%] LOSS: training ≈ 0.2504 validation ≈ 0.3151 (126%)
[ Info: [ 44%] LOSS: training ≈ 0.2503 validation ≈ 0.3149 (126%)
[ Info: [ 44%] LOSS: training ≈ 0.2501 validation ≈ 0.3147 (126%)
[ Info: [ 45%] LOSS: training ≈ 0.25   validation ≈ 0.3145 (126%)
[ Info: [ 46%] LOSS: training ≈ 0.2499 validation ≈ 0.3143 (126%)
[ Info: [ 46%] LOSS: training ≈ 0.2497 validation ≈ 0.3141 (126%)
[ Info: [ 46%] LOSS: training ≈ 0.2496 validation ≈ 0.3139 (126%)
[ Info: [ 47%] LOSS: training ≈ 0.2495 validation ≈ 0.3137 (126%)
[ Info: [ 48%] LOSS: training ≈ 0.2493 validation ≈ 0.3136 (126%)
[ Info: [ 48%] LOSS: training ≈ 0.2492 validation ≈ 0.3134 (126%)
[ Info: [ 48%] LOSS: training ≈ 0.2491 validation ≈ 0.3132 (126%)
[ Info: [ 49%] LOSS: training ≈ 0.249  validation ≈ 0.313  (126%)
[ Info: [ 50%] LOSS: training ≈ 0.2488 validation ≈ 0.3129 (126%)
[ Info: [ 50%] LOSS: training ≈ 0.2487 validation ≈ 0.3127 (126%)
[ Info: [ 50%] LOSS: training ≈ 0.2486 validation ≈ 0.3125 (126%)
[ Info: [ 51%] LOSS: training ≈ 0.2485 validation ≈ 0.3124 (126%)
[ Info: [ 52%] LOSS: training ≈ 0.2484 validation ≈ 0.3122 (126%)
[ Info: [ 52%] LOSS: training ≈ 0.2483 validation ≈ 0.3121 (126%)
[ Info: [ 52%] LOSS: training ≈ 0.2482 validation ≈ 0.3119 (126%)
[ Info: [ 53%] LOSS: training ≈ 0.2481 validation ≈ 0.3118 (126%)
[ Info: [ 54%] LOSS: training ≈ 0.248  validation ≈ 0.3116 (126%)
[ Info: [ 54%] LOSS: training ≈ 0.2479 validation ≈ 0.3115 (126%)
[ Info: [ 55%] LOSS: training ≈ 0.2478 validation ≈ 0.3114 (126%)
[ Info: [ 55%] LOSS: training ≈ 0.2477 validation ≈ 0.3112 (126%)
[ Info: [ 56%] LOSS: training ≈ 0.2476 validation ≈ 0.3111 (126%)
[ Info: [ 56%] LOSS: training ≈ 0.2475 validation ≈ 0.311  (126%)
[ Info: [ 56%] LOSS: training ≈ 0.2474 validation ≈ 0.3108 (126%)
[ Info: [ 57%] LOSS: training ≈ 0.2474 validation ≈ 0.3107 (126%)
[ Info: [ 57%] LOSS: training ≈ 0.2473 validation ≈ 0.3106 (126%)
[ Info: [ 58%] LOSS: training ≈ 0.2472 validation ≈ 0.3105 (126%)
[ Info: [ 58%] LOSS: training ≈ 0.2471 validation ≈ 0.3104 (126%)
[ Info: [ 59%] LOSS: training ≈ 0.247  validation ≈ 0.3102 (126%)
[ Info: [ 60%] LOSS: training ≈ 0.2469 validation ≈ 0.3101 (126%)
[ Info: [ 60%] LOSS: training ≈ 0.2469 validation ≈ 0.31   (126%)
[ Info: [ 60%] LOSS: training ≈ 0.2468 validation ≈ 0.3099 (126%)
[ Info: [ 61%] LOSS: training ≈ 0.2467 validation ≈ 0.3098 (126%)
[ Info: [ 62%] LOSS: training ≈ 0.2466 validation ≈ 0.3097 (126%)
[ Info: [ 62%] LOSS: training ≈ 0.2466 validation ≈ 0.3096 (126%)
[ Info: [ 62%] LOSS: training ≈ 0.2465 validation ≈ 0.3095 (126%)
[ Info: [ 63%] LOSS: training ≈ 0.2464 validation ≈ 0.3094 (126%)
[ Info: [ 64%] LOSS: training ≈ 0.2464 validation ≈ 0.3093 (126%)
[ Info: [ 64%] LOSS: training ≈ 0.2463 validation ≈ 0.3092 (126%)
[ Info: [ 64%] LOSS: training ≈ 0.2462 validation ≈ 0.3091 (126%)
[ Info: [ 65%] LOSS: training ≈ 0.2462 validation ≈ 0.309  (126%)
[ Info: [ 66%] LOSS: training ≈ 0.2461 validation ≈ 0.3089 (126%)
[ Info: [ 66%] LOSS: training ≈ 0.246  validation ≈ 0.3089 (126%)
[ Info: [ 66%] LOSS: training ≈ 0.246  validation ≈ 0.3088 (126%)
[ Info: [ 67%] LOSS: training ≈ 0.2459 validation ≈ 0.3087 (126%)
[ Info: [ 68%] LOSS: training ≈ 0.2459 validation ≈ 0.3086 (126%)
[ Info: [ 68%] LOSS: training ≈ 0.2458 validation ≈ 0.3085 (126%)
[ Info: [ 68%] LOSS: training ≈ 0.2458 validation ≈ 0.3084 (126%)
[ Info: [ 69%] LOSS: training ≈ 0.2457 validation ≈ 0.3084 (126%)
[ Info: [ 70%] LOSS: training ≈ 0.2456 validation ≈ 0.3083 (126%)
[ Info: [ 70%] LOSS: training ≈ 0.2456 validation ≈ 0.3082 (126%)
[ Info: [ 70%] LOSS: training ≈ 0.2455 validation ≈ 0.3081 (125%)
[ Info: [ 71%] LOSS: training ≈ 0.2455 validation ≈ 0.3081 (125%)
[ Info: [ 72%] LOSS: training ≈ 0.2454 validation ≈ 0.308  (125%)
[ Info: [ 72%] LOSS: training ≈ 0.2454 validation ≈ 0.3079 (125%)
[ Info: [ 72%] LOSS: training ≈ 0.2453 validation ≈ 0.3079 (125%)
[ Info: [ 73%] LOSS: training ≈ 0.2453 validation ≈ 0.3078 (125%)
[ Info: [ 74%] LOSS: training ≈ 0.2452 validation ≈ 0.3077 (125%)
[ Info: [ 74%] LOSS: training ≈ 0.2452 validation ≈ 0.3077 (125%)
[ Info: [ 74%] LOSS: training ≈ 0.2451 validation ≈ 0.3076 (125%)
[ Info: [ 75%] LOSS: training ≈ 0.2451 validation ≈ 0.3076 (125%)
[ Info: [ 76%] LOSS: training ≈ 0.2451 validation ≈ 0.3075 (125%)
[ Info: [ 76%] LOSS: training ≈ 0.245  validation ≈ 0.3074 (125%)
[ Info: [ 76%] LOSS: training ≈ 0.245  validation ≈ 0.3074 (125%)
[ Info: [ 77%] LOSS: training ≈ 0.2449 validation ≈ 0.3073 (125%)
[ Info: [ 78%] LOSS: training ≈ 0.2449 validation ≈ 0.3073 (125%)
[ Info: [ 78%] LOSS: training ≈ 0.2448 validation ≈ 0.3072 (125%)
[ Info: [ 78%] LOSS: training ≈ 0.2448 validation ≈ 0.3072 (125%)
[ Info: [ 79%] LOSS: training ≈ 0.2448 validation ≈ 0.3071 (125%)
[ Info: [ 80%] LOSS: training ≈ 0.2447 validation ≈ 0.3071 (125%)
[ Info: [ 80%] LOSS: training ≈ 0.2447 validation ≈ 0.307  (125%)
[ Info: [ 80%] LOSS: training ≈ 0.2446 validation ≈ 0.307  (125%)
[ Info: [ 81%] LOSS: training ≈ 0.2446 validation ≈ 0.3069 (125%)
[ Info: [ 82%] LOSS: training ≈ 0.2446 validation ≈ 0.3069 (125%)
[ Info: [ 82%] LOSS: training ≈ 0.2445 validation ≈ 0.3068 (125%)
[ Info: [ 82%] LOSS: training ≈ 0.2445 validation ≈ 0.3068 (125%)
[ Info: [ 83%] LOSS: training ≈ 0.2445 validation ≈ 0.3067 (125%)
[ Info: [ 84%] LOSS: training ≈ 0.2444 validation ≈ 0.3067 (125%)
[ Info: [ 84%] LOSS: training ≈ 0.2444 validation ≈ 0.3066 (125%)
[ Info: [ 84%] LOSS: training ≈ 0.2444 validation ≈ 0.3066 (125%)
[ Info: [ 85%] LOSS: training ≈ 0.2443 validation ≈ 0.3065 (125%)
[ Info: [ 86%] LOSS: training ≈ 0.2443 validation ≈ 0.3065 (125%)
[ Info: [ 86%] LOSS: training ≈ 0.2443 validation ≈ 0.3065 (125%)
[ Info: [ 86%] LOSS: training ≈ 0.2442 validation ≈ 0.3064 (125%)
[ Info: [ 87%] LOSS: training ≈ 0.2442 validation ≈ 0.3064 (125%)
[ Info: [ 88%] LOSS: training ≈ 0.2442 validation ≈ 0.3063 (125%)
[ Info: [ 88%] LOSS: training ≈ 0.2441 validation ≈ 0.3063 (125%)
[ Info: [ 88%] LOSS: training ≈ 0.2441 validation ≈ 0.3063 (125%)
[ Info: [ 89%] LOSS: training ≈ 0.2441 validation ≈ 0.3062 (125%)
[ Info: [ 90%] LOSS: training ≈ 0.2441 validation ≈ 0.3062 (125%)
[ Info: [ 90%] LOSS: training ≈ 0.244  validation ≈ 0.3062 (125%)
[ Info: [ 90%] LOSS: training ≈ 0.244  validation ≈ 0.3061 (125%)
[ Info: [ 91%] LOSS: training ≈ 0.244  validation ≈ 0.3061 (125%)
[ Info: [ 92%] LOSS: training ≈ 0.2439 validation ≈ 0.3061 (125%)
[ Info: [ 92%] LOSS: training ≈ 0.2439 validation ≈ 0.306  (125%)
[ Info: [ 92%] LOSS: training ≈ 0.2439 validation ≈ 0.306  (125%)
[ Info: [ 93%] LOSS: training ≈ 0.2439 validation ≈ 0.306  (125%)
[ Info: [ 94%] LOSS: training ≈ 0.2438 validation ≈ 0.3059 (125%)
[ Info: [ 94%] LOSS: training ≈ 0.2438 validation ≈ 0.3059 (125%)
[ Info: [ 94%] LOSS: training ≈ 0.2438 validation ≈ 0.3059 (125%)
[ Info: [ 95%] LOSS: training ≈ 0.2438 validation ≈ 0.3059 (125%)
[ Info: [ 96%] LOSS: training ≈ 0.2437 validation ≈ 0.3058 (125%)
[ Info: [ 96%] LOSS: training ≈ 0.2437 validation ≈ 0.3058 (125%)
[ Info: [ 96%] LOSS: training ≈ 0.2437 validation ≈ 0.3058 (125%)
[ Info: [ 97%] LOSS: training ≈ 0.2437 validation ≈ 0.3057 (125%)
[ Info: [ 98%] LOSS: training ≈ 0.2436 validation ≈ 0.3057 (125%)
[ Info: [ 98%] LOSS: training ≈ 0.2436 validation ≈ 0.3057 (125%)
[ Info: [ 98%] LOSS: training ≈ 0.2436 validation ≈ 0.3057 (125%)
[ Info: [ 99%] LOSS: training ≈ 0.2436 validation ≈ 0.3056 (125%)
[ Info: [100%] LOSS: training ≈ 0.2435 validation ≈ 0.3056 (125%)
[ Info: [100%] LOSS: training ≈ 0.2435 validation ≈ 0.3056 (125%)
[ 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 ≈ 0.7614
[ Info: Returning model with 1 variables - mcc ≈ 0.7614
┌ 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. ≈ 0.8
[ Info: [ 4 vars.] MCC val. ≈ 0.835
[ Info: [ 5 vars.] MCC val. ≈ 0.842
[ Info: [ 6 vars.] MCC val. ≈ 0.855
[ Info: [ 7 vars.] MCC val. ≈ 0.862
[ Info: Optimal var. pool: [1, 12, 8, 3, 18, 4, 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. ≈ 0.722
[ Info: [ 2 vars.] MCC val. ≈ 0.724
[ Info: [ 3 vars.] MCC val. ≈ 0.732
[ Info: [ 4 vars.] MCC val. ≈ 0.739
[ Info: Optimal var. pool: [9, 15, 13, 4]
┌ 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. ≈ 0.828
[ Info: [17 vars.] MCC val. ≈ 0.849
[ Info: Optimal var. pool: [1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 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. ≈ 0.801
[ Info: [ 7 vars.] MCC val. ≈ 0.828
[ Info: Optimal var. pool: [1, 3, 4, 5, 6, 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. ≈ 0.718
[ Info: [ 4 vars.] MCC val. ≈ 0.752
[ Info: [ 5 vars.] MCC val. ≈ 0.767
[ Info: [ 6 vars.] MCC val. ≈ 0.78
[ Info: Optimal var. pool: [12, 13, 6, 3, 8, 1]
┌ 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. ≈ 0.811
[ Info: Optimal var. pool: [8]
Test Summary: | Pass  Total      Time
Package       |  375    375  21m56.7s
     Testing SDeMo tests passed 

Testing completed after 1363.75s

PkgEval succeeded after 1442.28s