Package evaluation to test SDeMo on Julia 1.11.7 (58327cce5e*) started at 2025-10-28T21:27:40.666


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

Installing PkgEval dependencies (TestEnv)...

Set-up completed after 8.5s


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

Installing SDeMo...
   Resolving package versions...
    Updating `~/.julia/environments/v1.11/Project.toml`
  [3e5feb82] + SDeMo v1.5.2
    Updating `~/.julia/environments/v1.11/Manifest.toml`
  [66dad0bd] + AliasTables v1.1.3
  [7d9fca2a] + Arpack v0.5.4
  [9a962f9c] + DataAPI v1.16.0
  [864edb3b] + DataStructures v0.19.1
  [31c24e10] + Distributions v0.25.122
  [ffbed154] + DocStringExtensions v0.9.5
  [1a297f60] + FillArrays v1.14.0
  [34004b35] + HypergeometricFunctions v0.3.28
  [92d709cd] + IrrationalConstants v0.2.6
  [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 v0.11.36
  [69de0a69] + Parsers v2.8.3
⌅ [aea7be01] + PrecompileTools v1.2.1
  [21216c6a] + Preferences v1.5.0
  [43287f4e] + PtrArrays v1.3.0
  [1fd47b50] + QuadGK v2.11.2
  [189a3867] + Reexport v1.2.2
  [79098fc4] + Rmath v0.9.0
  [3e5feb82] + SDeMo v1.5.2
  [a2af1166] + SortingAlgorithms v1.2.2
  [276daf66] + SpecialFunctions v2.6.1
  [10745b16] + Statistics v1.11.1
  [82ae8749] + StatsAPI v1.7.1
  [2913bbd2] + StatsBase v0.34.7
  [4c63d2b9] + StatsFuns v1.5.2
  [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 v1.6.0
  [7b1f6079] + FileWatching v1.11.0
  [b27032c2] + LibCURL v0.6.4
  [76f85450] + LibGit2 v1.11.0
  [8f399da3] + Libdl v1.11.0
  [37e2e46d] + LinearAlgebra v1.11.0
  [56ddb016] + Logging v1.11.0
  [d6f4376e] + Markdown v1.11.0
  [a63ad114] + Mmap v1.11.0
  [ca575930] + NetworkOptions v1.2.0
  [44cfe95a] + Pkg v1.11.0
  [de0858da] + Printf v1.11.0
  [9a3f8284] + Random v1.11.0
  [ea8e919c] + SHA v0.7.0
  [9e88b42a] + Serialization v1.11.0
  [2f01184e] + SparseArrays 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 v1.1.1+0
  [deac9b47] + LibCURL_jll v8.6.0+0
  [e37daf67] + LibGit2_jll v1.7.2+0
  [29816b5a] + LibSSH2_jll v1.11.0+1
  [c8ffd9c3] + MbedTLS_jll v2.28.6+0
  [14a3606d] + MozillaCACerts_jll v2023.12.12
  [4536629a] + OpenBLAS_jll v0.3.27+1
  [05823500] + OpenLibm_jll v0.8.5+0
  [bea87d4a] + SuiteSparse_jll v7.7.0+0
  [83775a58] + Zlib_jll v1.2.13+1
  [8e850b90] + libblastrampoline_jll v5.11.0+0
  [8e850ede] + nghttp2_jll v1.59.0+0
  [3f19e933] + p7zip_jll v17.4.0+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 5.16s


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

Precompiling PkgEval dependencies...

Precompiling package dependencies...

Precompilation completed after 23.55s


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

     Testing SDeMo
      Status `/tmp/jl_o6AYFy/Project.toml`
  [3e5feb82] SDeMo v1.5.2
  [10745b16] Statistics v1.11.1
  [f8b46487] TestItemRunner v1.1.0
  [8dfed614] Test v1.11.0
      Status `/tmp/jl_o6AYFy/Manifest.toml`
  [66dad0bd] AliasTables v1.1.3
  [7d9fca2a] Arpack v0.5.4
  [9a962f9c] DataAPI v1.16.0
  [864edb3b] DataStructures v0.19.1
  [31c24e10] Distributions v0.25.122
  [ffbed154] DocStringExtensions v0.9.5
  [1a297f60] FillArrays v1.14.0
  [34004b35] HypergeometricFunctions v0.3.28
  [92d709cd] IrrationalConstants v0.2.6
  [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 v0.11.36
  [69de0a69] Parsers v2.8.3
⌅ [aea7be01] PrecompileTools v1.2.1
  [21216c6a] Preferences v1.5.0
  [43287f4e] PtrArrays v1.3.0
  [1fd47b50] QuadGK v2.11.2
  [189a3867] Reexport v1.2.2
  [79098fc4] Rmath v0.9.0
  [3e5feb82] SDeMo v1.5.2
  [a2af1166] SortingAlgorithms v1.2.2
  [276daf66] SpecialFunctions v2.6.1
  [10745b16] Statistics v1.11.1
  [82ae8749] StatsAPI v1.7.1
  [2913bbd2] StatsBase v0.34.7
  [4c63d2b9] StatsFuns v1.5.2
  [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 v1.6.0
  [7b1f6079] FileWatching v1.11.0
  [b77e0a4c] InteractiveUtils v1.11.0
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2 v1.11.0
  [8f399da3] Libdl v1.11.0
  [37e2e46d] LinearAlgebra v1.11.0
  [56ddb016] Logging v1.11.0
  [d6f4376e] Markdown v1.11.0
  [a63ad114] Mmap v1.11.0
  [ca575930] NetworkOptions v1.2.0
  [44cfe95a] Pkg v1.11.0
  [de0858da] Printf v1.11.0
  [9a3f8284] Random v1.11.0
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization v1.11.0
  [2f01184e] SparseArrays 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 v1.1.1+0
  [deac9b47] LibCURL_jll v8.6.0+0
  [e37daf67] LibGit2_jll v1.7.2+0
  [29816b5a] LibSSH2_jll v1.11.0+1
  [c8ffd9c3] MbedTLS_jll v2.28.6+0
  [14a3606d] MozillaCACerts_jll v2023.12.12
  [4536629a] OpenBLAS_jll v0.3.27+1
  [05823500] OpenLibm_jll v0.8.5+0
  [bea87d4a] SuiteSparse_jll v7.7.0+0
  [83775a58] Zlib_jll v1.2.13+1
  [8e850b90] libblastrampoline_jll v5.11.0+0
  [8e850ede] nghttp2_jll v1.59.0+0
  [3f19e933] p7zip_jll v17.4.0+2
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading.
     Testing Running tests...
[ Info: Baseline mcc: -2.8367742685852565e-17
[ Info: Optimal 1 variables model - mcc ≈ 0.7306
[ Info: Optimal 2 variables model - mcc ≈ 0.7631
[ Info: Optimal 3 variables model - mcc ≈ 0.7695
[ Info: Optimal 4 variables model - mcc ≈ 0.7813
[ Info: Optimal 5 variables model - mcc ≈ 0.7903
[ Info: Optimal 6 variables model - mcc ≈ 0.8046
[ Info: Optimal 7 variables model - mcc ≈ 0.8052
[ Info: Returning model with 7 variables - mcc ≈ 0.8052
[ Info: [  0%] LOSS: training ≈ 0.4911 validation ≈ 0.5096 (104%)
[ Info: [  1%] LOSS: training ≈ 0.4151 validation ≈ 0.4491 (108%)
[ Info: [  2%] LOSS: training ≈ 0.3777 validation ≈ 0.4192 (111%)
[ Info: [  2%] LOSS: training ≈ 0.3555 validation ≈ 0.4014 (113%)
[ Info: [  2%] LOSS: training ≈ 0.3407 validation ≈ 0.3896 (114%)
[ Info: [  3%] LOSS: training ≈ 0.3301 validation ≈ 0.3811 (115%)
[ Info: [  4%] LOSS: training ≈ 0.322  validation ≈ 0.3747 (116%)
[ Info: [  4%] LOSS: training ≈ 0.3156 validation ≈ 0.3695 (117%)
[ Info: [  4%] LOSS: training ≈ 0.3103 validation ≈ 0.3653 (118%)
[ Info: [  5%] LOSS: training ≈ 0.3059 validation ≈ 0.3618 (118%)
[ Info: [  6%] LOSS: training ≈ 0.3021 validation ≈ 0.3588 (119%)
[ Info: [  6%] LOSS: training ≈ 0.2987 validation ≈ 0.3562 (119%)
[ Info: [  6%] LOSS: training ≈ 0.2958 validation ≈ 0.3539 (120%)
[ Info: [  7%] LOSS: training ≈ 0.2932 validation ≈ 0.3518 (120%)
[ Info: [  8%] LOSS: training ≈ 0.2908 validation ≈ 0.35   (120%)
[ Info: [  8%] LOSS: training ≈ 0.2887 validation ≈ 0.3483 (121%)
[ Info: [  8%] LOSS: training ≈ 0.2867 validation ≈ 0.3467 (121%)
[ Info: [  9%] LOSS: training ≈ 0.2849 validation ≈ 0.3453 (121%)
[ Info: [ 10%] LOSS: training ≈ 0.2832 validation ≈ 0.3441 (121%)
[ Info: [ 10%] LOSS: training ≈ 0.2816 validation ≈ 0.3429 (122%)
[ Info: [ 10%] LOSS: training ≈ 0.2802 validation ≈ 0.3417 (122%)
[ Info: [ 11%] LOSS: training ≈ 0.2788 validation ≈ 0.3407 (122%)
[ Info: [ 12%] LOSS: training ≈ 0.2775 validation ≈ 0.3397 (122%)
[ Info: [ 12%] LOSS: training ≈ 0.2763 validation ≈ 0.3388 (123%)
[ Info: [ 12%] LOSS: training ≈ 0.2752 validation ≈ 0.3379 (123%)
[ Info: [ 13%] LOSS: training ≈ 0.2741 validation ≈ 0.3371 (123%)
[ Info: [ 14%] LOSS: training ≈ 0.273  validation ≈ 0.3363 (123%)
[ Info: [ 14%] LOSS: training ≈ 0.2721 validation ≈ 0.3356 (123%)
[ Info: [ 14%] LOSS: training ≈ 0.2711 validation ≈ 0.3349 (124%)
[ Info: [ 15%] LOSS: training ≈ 0.2703 validation ≈ 0.3342 (124%)
[ Info: [ 16%] LOSS: training ≈ 0.2694 validation ≈ 0.3336 (124%)
[ Info: [ 16%] LOSS: training ≈ 0.2686 validation ≈ 0.333  (124%)
[ Info: [ 16%] LOSS: training ≈ 0.2678 validation ≈ 0.3324 (124%)
[ Info: [ 17%] LOSS: training ≈ 0.2671 validation ≈ 0.3318 (124%)
[ Info: [ 18%] LOSS: training ≈ 0.2664 validation ≈ 0.3313 (124%)
[ Info: [ 18%] LOSS: training ≈ 0.2657 validation ≈ 0.3308 (124%)
[ Info: [ 18%] LOSS: training ≈ 0.265  validation ≈ 0.3302 (125%)
[ Info: [ 19%] LOSS: training ≈ 0.2644 validation ≈ 0.3298 (125%)
[ Info: [ 20%] LOSS: training ≈ 0.2638 validation ≈ 0.3293 (125%)
[ Info: [ 20%] LOSS: training ≈ 0.2632 validation ≈ 0.3288 (125%)
[ Info: [ 20%] LOSS: training ≈ 0.2626 validation ≈ 0.3284 (125%)
[ Info: [ 21%] LOSS: training ≈ 0.2621 validation ≈ 0.328  (125%)
[ Info: [ 22%] LOSS: training ≈ 0.2616 validation ≈ 0.3275 (125%)
[ Info: [ 22%] LOSS: training ≈ 0.2611 validation ≈ 0.3271 (125%)
[ Info: [ 22%] LOSS: training ≈ 0.2606 validation ≈ 0.3267 (125%)
[ Info: [ 23%] LOSS: training ≈ 0.2601 validation ≈ 0.3264 (125%)
[ Info: [ 24%] LOSS: training ≈ 0.2597 validation ≈ 0.326  (126%)
[ Info: [ 24%] LOSS: training ≈ 0.2592 validation ≈ 0.3256 (126%)
[ Info: [ 24%] LOSS: training ≈ 0.2588 validation ≈ 0.3253 (126%)
[ Info: [ 25%] LOSS: training ≈ 0.2584 validation ≈ 0.3249 (126%)
[ Info: [ 26%] LOSS: training ≈ 0.258  validation ≈ 0.3246 (126%)
[ Info: [ 26%] LOSS: training ≈ 0.2576 validation ≈ 0.3243 (126%)
[ Info: [ 26%] LOSS: training ≈ 0.2572 validation ≈ 0.324  (126%)
[ Info: [ 27%] LOSS: training ≈ 0.2568 validation ≈ 0.3237 (126%)
[ Info: [ 28%] LOSS: training ≈ 0.2565 validation ≈ 0.3234 (126%)
[ Info: [ 28%] LOSS: training ≈ 0.2562 validation ≈ 0.3231 (126%)
[ Info: [ 28%] LOSS: training ≈ 0.2558 validation ≈ 0.3228 (126%)
[ Info: [ 29%] LOSS: training ≈ 0.2555 validation ≈ 0.3225 (126%)
[ Info: [ 30%] LOSS: training ≈ 0.2552 validation ≈ 0.3222 (126%)
[ Info: [ 30%] LOSS: training ≈ 0.2549 validation ≈ 0.322  (126%)
[ Info: [ 30%] LOSS: training ≈ 0.2546 validation ≈ 0.3217 (126%)
[ Info: [ 31%] LOSS: training ≈ 0.2543 validation ≈ 0.3214 (126%)
[ Info: [ 32%] LOSS: training ≈ 0.254  validation ≈ 0.3212 (126%)
[ Info: [ 32%] LOSS: training ≈ 0.2537 validation ≈ 0.3209 (126%)
[ Info: [ 32%] LOSS: training ≈ 0.2535 validation ≈ 0.3207 (127%)
[ Info: [ 33%] LOSS: training ≈ 0.2532 validation ≈ 0.3205 (127%)
[ Info: [ 34%] LOSS: training ≈ 0.253  validation ≈ 0.3202 (127%)
[ Info: [ 34%] LOSS: training ≈ 0.2527 validation ≈ 0.32   (127%)
[ Info: [ 34%] LOSS: training ≈ 0.2525 validation ≈ 0.3198 (127%)
[ Info: [ 35%] LOSS: training ≈ 0.2523 validation ≈ 0.3196 (127%)
[ Info: [ 36%] LOSS: training ≈ 0.252  validation ≈ 0.3194 (127%)
[ Info: [ 36%] LOSS: training ≈ 0.2518 validation ≈ 0.3192 (127%)
[ Info: [ 36%] LOSS: training ≈ 0.2516 validation ≈ 0.319  (127%)
[ Info: [ 37%] LOSS: training ≈ 0.2514 validation ≈ 0.3188 (127%)
[ Info: [ 38%] LOSS: training ≈ 0.2512 validation ≈ 0.3186 (127%)
[ Info: [ 38%] LOSS: training ≈ 0.251  validation ≈ 0.3184 (127%)
[ Info: [ 38%] LOSS: training ≈ 0.2508 validation ≈ 0.3182 (127%)
[ Info: [ 39%] LOSS: training ≈ 0.2506 validation ≈ 0.318  (127%)
[ Info: [ 40%] LOSS: training ≈ 0.2505 validation ≈ 0.3178 (127%)
[ Info: [ 40%] LOSS: training ≈ 0.2503 validation ≈ 0.3176 (127%)
[ Info: [ 40%] LOSS: training ≈ 0.2501 validation ≈ 0.3175 (127%)
[ Info: [ 41%] LOSS: training ≈ 0.2499 validation ≈ 0.3173 (127%)
[ Info: [ 42%] LOSS: training ≈ 0.2498 validation ≈ 0.3171 (127%)
[ Info: [ 42%] LOSS: training ≈ 0.2496 validation ≈ 0.3169 (127%)
[ Info: [ 42%] LOSS: training ≈ 0.2495 validation ≈ 0.3168 (127%)
[ Info: [ 43%] LOSS: training ≈ 0.2493 validation ≈ 0.3166 (127%)
[ Info: [ 44%] LOSS: training ≈ 0.2492 validation ≈ 0.3165 (127%)
[ Info: [ 44%] LOSS: training ≈ 0.249  validation ≈ 0.3163 (127%)
[ Info: [ 44%] LOSS: training ≈ 0.2489 validation ≈ 0.3162 (127%)
[ Info: [ 45%] LOSS: training ≈ 0.2487 validation ≈ 0.316  (127%)
[ Info: [ 46%] LOSS: training ≈ 0.2486 validation ≈ 0.3159 (127%)
[ Info: [ 46%] LOSS: training ≈ 0.2485 validation ≈ 0.3157 (127%)
[ Info: [ 46%] LOSS: training ≈ 0.2483 validation ≈ 0.3156 (127%)
[ Info: [ 47%] LOSS: training ≈ 0.2482 validation ≈ 0.3154 (127%)
[ Info: [ 48%] LOSS: training ≈ 0.2481 validation ≈ 0.3153 (127%)
[ Info: [ 48%] LOSS: training ≈ 0.248  validation ≈ 0.3152 (127%)
[ Info: [ 48%] LOSS: training ≈ 0.2479 validation ≈ 0.315  (127%)
[ Info: [ 49%] LOSS: training ≈ 0.2477 validation ≈ 0.3149 (127%)
[ Info: [ 50%] LOSS: training ≈ 0.2476 validation ≈ 0.3148 (127%)
[ Info: [ 50%] LOSS: training ≈ 0.2475 validation ≈ 0.3146 (127%)
[ Info: [ 50%] LOSS: training ≈ 0.2474 validation ≈ 0.3145 (127%)
[ Info: [ 51%] LOSS: training ≈ 0.2473 validation ≈ 0.3144 (127%)
[ Info: [ 52%] LOSS: training ≈ 0.2472 validation ≈ 0.3143 (127%)
[ Info: [ 52%] LOSS: training ≈ 0.2471 validation ≈ 0.3142 (127%)
[ Info: [ 52%] LOSS: training ≈ 0.247  validation ≈ 0.314  (127%)
[ Info: [ 53%] LOSS: training ≈ 0.2469 validation ≈ 0.3139 (127%)
[ Info: [ 54%] LOSS: training ≈ 0.2468 validation ≈ 0.3138 (127%)
[ Info: [ 54%] LOSS: training ≈ 0.2467 validation ≈ 0.3137 (127%)
[ Info: [ 55%] LOSS: training ≈ 0.2466 validation ≈ 0.3136 (127%)
[ Info: [ 55%] LOSS: training ≈ 0.2466 validation ≈ 0.3135 (127%)
[ Info: [ 56%] LOSS: training ≈ 0.2465 validation ≈ 0.3134 (127%)
[ Info: [ 56%] LOSS: training ≈ 0.2464 validation ≈ 0.3133 (127%)
[ Info: [ 56%] LOSS: training ≈ 0.2463 validation ≈ 0.3132 (127%)
[ Info: [ 57%] LOSS: training ≈ 0.2462 validation ≈ 0.3131 (127%)
[ Info: [ 57%] LOSS: training ≈ 0.2461 validation ≈ 0.313  (127%)
[ Info: [ 58%] LOSS: training ≈ 0.2461 validation ≈ 0.3129 (127%)
[ Info: [ 58%] LOSS: training ≈ 0.246  validation ≈ 0.3128 (127%)
[ Info: [ 59%] LOSS: training ≈ 0.2459 validation ≈ 0.3127 (127%)
[ Info: [ 60%] LOSS: training ≈ 0.2458 validation ≈ 0.3126 (127%)
[ Info: [ 60%] LOSS: training ≈ 0.2458 validation ≈ 0.3125 (127%)
[ Info: [ 60%] LOSS: training ≈ 0.2457 validation ≈ 0.3124 (127%)
[ Info: [ 61%] LOSS: training ≈ 0.2456 validation ≈ 0.3123 (127%)
[ Info: [ 62%] LOSS: training ≈ 0.2456 validation ≈ 0.3122 (127%)
[ Info: [ 62%] LOSS: training ≈ 0.2455 validation ≈ 0.3121 (127%)
[ Info: [ 62%] LOSS: training ≈ 0.2454 validation ≈ 0.312  (127%)
[ Info: [ 63%] LOSS: training ≈ 0.2454 validation ≈ 0.3119 (127%)
[ Info: [ 64%] LOSS: training ≈ 0.2453 validation ≈ 0.3119 (127%)
[ Info: [ 64%] LOSS: training ≈ 0.2453 validation ≈ 0.3118 (127%)
[ Info: [ 64%] LOSS: training ≈ 0.2452 validation ≈ 0.3117 (127%)
[ Info: [ 65%] LOSS: training ≈ 0.2451 validation ≈ 0.3116 (127%)
[ Info: [ 66%] LOSS: training ≈ 0.2451 validation ≈ 0.3115 (127%)
[ Info: [ 66%] LOSS: training ≈ 0.245  validation ≈ 0.3114 (127%)
[ Info: [ 66%] LOSS: training ≈ 0.245  validation ≈ 0.3114 (127%)
[ Info: [ 67%] LOSS: training ≈ 0.2449 validation ≈ 0.3113 (127%)
[ Info: [ 68%] LOSS: training ≈ 0.2449 validation ≈ 0.3112 (127%)
[ Info: [ 68%] LOSS: training ≈ 0.2448 validation ≈ 0.3111 (127%)
[ Info: [ 68%] LOSS: training ≈ 0.2448 validation ≈ 0.3111 (127%)
[ Info: [ 69%] LOSS: training ≈ 0.2447 validation ≈ 0.311  (127%)
[ Info: [ 70%] LOSS: training ≈ 0.2447 validation ≈ 0.3109 (127%)
[ Info: [ 70%] LOSS: training ≈ 0.2446 validation ≈ 0.3108 (127%)
[ Info: [ 70%] LOSS: training ≈ 0.2446 validation ≈ 0.3108 (127%)
[ Info: [ 71%] LOSS: training ≈ 0.2445 validation ≈ 0.3107 (127%)
[ Info: [ 72%] LOSS: training ≈ 0.2445 validation ≈ 0.3106 (127%)
[ Info: [ 72%] LOSS: training ≈ 0.2444 validation ≈ 0.3106 (127%)
[ Info: [ 72%] LOSS: training ≈ 0.2444 validation ≈ 0.3105 (127%)
[ Info: [ 73%] LOSS: training ≈ 0.2443 validation ≈ 0.3104 (127%)
[ Info: [ 74%] LOSS: training ≈ 0.2443 validation ≈ 0.3104 (127%)
[ Info: [ 74%] LOSS: training ≈ 0.2443 validation ≈ 0.3103 (127%)
[ Info: [ 74%] LOSS: training ≈ 0.2442 validation ≈ 0.3102 (127%)
[ Info: [ 75%] LOSS: training ≈ 0.2442 validation ≈ 0.3102 (127%)
[ Info: [ 76%] LOSS: training ≈ 0.2441 validation ≈ 0.3101 (127%)
[ Info: [ 76%] LOSS: training ≈ 0.2441 validation ≈ 0.3101 (127%)
[ Info: [ 76%] LOSS: training ≈ 0.2441 validation ≈ 0.31   (127%)
[ Info: [ 77%] LOSS: training ≈ 0.244  validation ≈ 0.3099 (127%)
[ Info: [ 78%] LOSS: training ≈ 0.244  validation ≈ 0.3099 (127%)
[ Info: [ 78%] LOSS: training ≈ 0.2439 validation ≈ 0.3098 (127%)
[ Info: [ 78%] LOSS: training ≈ 0.2439 validation ≈ 0.3098 (127%)
[ Info: [ 79%] LOSS: training ≈ 0.2439 validation ≈ 0.3097 (127%)
[ Info: [ 80%] LOSS: training ≈ 0.2438 validation ≈ 0.3096 (127%)
[ Info: [ 80%] LOSS: training ≈ 0.2438 validation ≈ 0.3096 (127%)
[ Info: [ 80%] LOSS: training ≈ 0.2438 validation ≈ 0.3095 (127%)
[ Info: [ 81%] LOSS: training ≈ 0.2437 validation ≈ 0.3095 (127%)
[ Info: [ 82%] LOSS: training ≈ 0.2437 validation ≈ 0.3094 (127%)
[ Info: [ 82%] LOSS: training ≈ 0.2437 validation ≈ 0.3094 (127%)
[ Info: [ 82%] LOSS: training ≈ 0.2436 validation ≈ 0.3093 (127%)
[ Info: [ 83%] LOSS: training ≈ 0.2436 validation ≈ 0.3093 (127%)
[ Info: [ 84%] LOSS: training ≈ 0.2436 validation ≈ 0.3092 (127%)
[ Info: [ 84%] LOSS: training ≈ 0.2436 validation ≈ 0.3092 (127%)
[ Info: [ 84%] LOSS: training ≈ 0.2435 validation ≈ 0.3091 (127%)
[ Info: [ 85%] LOSS: training ≈ 0.2435 validation ≈ 0.3091 (127%)
[ Info: [ 86%] LOSS: training ≈ 0.2435 validation ≈ 0.309  (127%)
[ Info: [ 86%] LOSS: training ≈ 0.2434 validation ≈ 0.309  (127%)
[ Info: [ 86%] LOSS: training ≈ 0.2434 validation ≈ 0.3089 (127%)
[ Info: [ 87%] LOSS: training ≈ 0.2434 validation ≈ 0.3089 (127%)
[ Info: [ 88%] LOSS: training ≈ 0.2434 validation ≈ 0.3088 (127%)
[ Info: [ 88%] LOSS: training ≈ 0.2433 validation ≈ 0.3088 (127%)
[ Info: [ 88%] LOSS: training ≈ 0.2433 validation ≈ 0.3087 (127%)
[ Info: [ 89%] LOSS: training ≈ 0.2433 validation ≈ 0.3087 (127%)
[ Info: [ 90%] LOSS: training ≈ 0.2433 validation ≈ 0.3087 (127%)
[ Info: [ 90%] LOSS: training ≈ 0.2432 validation ≈ 0.3086 (127%)
[ Info: [ 90%] LOSS: training ≈ 0.2432 validation ≈ 0.3086 (127%)
[ Info: [ 91%] LOSS: training ≈ 0.2432 validation ≈ 0.3085 (127%)
[ Info: [ 92%] LOSS: training ≈ 0.2432 validation ≈ 0.3085 (127%)
[ Info: [ 92%] LOSS: training ≈ 0.2431 validation ≈ 0.3084 (127%)
[ Info: [ 92%] LOSS: training ≈ 0.2431 validation ≈ 0.3084 (127%)
[ Info: [ 93%] LOSS: training ≈ 0.2431 validation ≈ 0.3084 (127%)
[ Info: [ 94%] LOSS: training ≈ 0.2431 validation ≈ 0.3083 (127%)
[ Info: [ 94%] LOSS: training ≈ 0.2431 validation ≈ 0.3083 (127%)
[ Info: [ 94%] LOSS: training ≈ 0.243  validation ≈ 0.3082 (127%)
[ Info: [ 95%] LOSS: training ≈ 0.243  validation ≈ 0.3082 (127%)
[ Info: [ 96%] LOSS: training ≈ 0.243  validation ≈ 0.3082 (127%)
[ Info: [ 96%] LOSS: training ≈ 0.243  validation ≈ 0.3081 (127%)
[ Info: [ 96%] LOSS: training ≈ 0.243  validation ≈ 0.3081 (127%)
[ Info: [ 97%] LOSS: training ≈ 0.2429 validation ≈ 0.308  (127%)
[ Info: [ 98%] LOSS: training ≈ 0.2429 validation ≈ 0.308  (127%)
[ Info: [ 98%] LOSS: training ≈ 0.2429 validation ≈ 0.308  (127%)
[ Info: [ 98%] LOSS: training ≈ 0.2429 validation ≈ 0.3079 (127%)
[ Info: [ 99%] LOSS: training ≈ 0.2429 validation ≈ 0.3079 (127%)
[ Info: [100%] LOSS: training ≈ 0.2428 validation ≈ 0.3079 (127%)
[ Info: [100%] LOSS: training ≈ 0.2428 validation ≈ 0.3078 (127%)
[ Info: [  0%] LOSS: training ≈ 0.4215
[ Info: [  1%] LOSS: training ≈ 0.3806
[ Info: [  2%] LOSS: training ≈ 0.3564
[ Info: [  2%] LOSS: training ≈ 0.3399
[ Info: [  2%] LOSS: training ≈ 0.3279
[ Info: [  3%] LOSS: training ≈ 0.3185
[ Info: [  4%] LOSS: training ≈ 0.311 
[ Info: [  4%] LOSS: training ≈ 0.3048
[ Info: [  4%] LOSS: training ≈ 0.2996
[ Info: [  5%] LOSS: training ≈ 0.2952
[ Info: [  6%] LOSS: training ≈ 0.2914
[ Info: [  6%] LOSS: training ≈ 0.2881
[ Info: [  6%] LOSS: training ≈ 0.2852
[ Info: [  7%] LOSS: training ≈ 0.2826
[ Info: [  8%] LOSS: training ≈ 0.2802
[ Info: [  8%] LOSS: training ≈ 0.2782
[ Info: [  8%] LOSS: training ≈ 0.2763
[ Info: [  9%] LOSS: training ≈ 0.2746
[ Info: [ 10%] LOSS: training ≈ 0.2731
[ Info: [ 10%] LOSS: training ≈ 0.2717
[ Info: [ 10%] LOSS: training ≈ 0.2704
[ Info: [ 11%] LOSS: training ≈ 0.2692
[ Info: [ 12%] LOSS: training ≈ 0.2681
[ Info: [ 12%] LOSS: training ≈ 0.2671
[ Info: [ 12%] LOSS: training ≈ 0.2662
[ Info: [ 13%] LOSS: training ≈ 0.2654
[ Info: [ 14%] LOSS: training ≈ 0.2646
[ Info: [ 14%] LOSS: training ≈ 0.2639
[ Info: [ 14%] LOSS: training ≈ 0.2632
[ Info: [ 15%] LOSS: training ≈ 0.2626
[ Info: [ 16%] LOSS: training ≈ 0.262 
[ Info: [ 16%] LOSS: training ≈ 0.2614
[ Info: [ 16%] LOSS: training ≈ 0.2609
[ Info: [ 17%] LOSS: training ≈ 0.2605
[ Info: [ 18%] LOSS: training ≈ 0.26  
[ Info: [ 18%] LOSS: training ≈ 0.2596
[ Info: [ 18%] LOSS: training ≈ 0.2592
[ Info: [ 19%] LOSS: training ≈ 0.2589
[ Info: [ 20%] LOSS: training ≈ 0.2585
[ Info: [ 20%] LOSS: training ≈ 0.2582
[ Info: [ 20%] LOSS: training ≈ 0.2579
[ Info: [ 21%] LOSS: training ≈ 0.2576
[ Info: [ 22%] LOSS: training ≈ 0.2573
[ Info: [ 22%] LOSS: training ≈ 0.2571
[ Info: [ 22%] LOSS: training ≈ 0.2568
[ Info: [ 23%] LOSS: training ≈ 0.2566
[ Info: [ 24%] LOSS: training ≈ 0.2564
[ Info: [ 24%] LOSS: training ≈ 0.2562
[ Info: [ 24%] LOSS: training ≈ 0.256 
[ Info: [ 25%] LOSS: training ≈ 0.2558
[ Info: [ 26%] LOSS: training ≈ 0.2557
[ Info: [ 26%] LOSS: training ≈ 0.2555
[ Info: [ 26%] LOSS: training ≈ 0.2554
[ Info: [ 27%] LOSS: training ≈ 0.2552
[ Info: [ 28%] LOSS: training ≈ 0.2551
[ Info: [ 28%] LOSS: training ≈ 0.255 
[ Info: [ 28%] LOSS: training ≈ 0.2548
[ Info: [ 29%] LOSS: training ≈ 0.2547
[ Info: [ 30%] LOSS: training ≈ 0.2546
[ Info: [ 30%] LOSS: training ≈ 0.2545
[ Info: [ 30%] LOSS: training ≈ 0.2544
[ Info: [ 31%] LOSS: training ≈ 0.2543
[ Info: [ 32%] LOSS: training ≈ 0.2542
[ Info: [ 32%] LOSS: training ≈ 0.2541
[ Info: [ 32%] LOSS: training ≈ 0.2541
[ Info: [ 33%] LOSS: training ≈ 0.254 
[ Info: [ 34%] LOSS: training ≈ 0.2539
[ Info: [ 34%] LOSS: training ≈ 0.2538
[ Info: [ 34%] LOSS: training ≈ 0.2538
[ Info: [ 35%] LOSS: training ≈ 0.2537
[ Info: [ 36%] LOSS: training ≈ 0.2536
[ Info: [ 36%] LOSS: training ≈ 0.2536
[ Info: [ 36%] LOSS: training ≈ 0.2535
[ Info: [ 37%] LOSS: training ≈ 0.2535
[ Info: [ 38%] LOSS: training ≈ 0.2534
[ Info: [ 38%] LOSS: training ≈ 0.2534
[ Info: [ 38%] LOSS: training ≈ 0.2533
[ Info: [ 39%] LOSS: training ≈ 0.2533
[ Info: [ 40%] LOSS: training ≈ 0.2532
[ Info: [ 40%] LOSS: training ≈ 0.2532
[ Info: [ 40%] LOSS: training ≈ 0.2532
[ Info: [ 41%] LOSS: training ≈ 0.2531
[ Info: [ 42%] LOSS: training ≈ 0.2531
[ Info: [ 42%] LOSS: training ≈ 0.2531
[ Info: [ 42%] LOSS: training ≈ 0.253 
[ Info: [ 43%] LOSS: training ≈ 0.253 
[ Info: [ 44%] LOSS: training ≈ 0.253 
[ Info: [ 44%] LOSS: training ≈ 0.2529
[ Info: [ 44%] LOSS: training ≈ 0.2529
[ Info: [ 45%] LOSS: training ≈ 0.2529
[ Info: [ 46%] LOSS: training ≈ 0.2529
[ Info: [ 46%] LOSS: training ≈ 0.2528
[ Info: [ 46%] LOSS: training ≈ 0.2528
[ Info: [ 47%] LOSS: training ≈ 0.2528
[ Info: [ 48%] LOSS: training ≈ 0.2528
[ Info: [ 48%] LOSS: training ≈ 0.2527
[ Info: [ 48%] LOSS: training ≈ 0.2527
[ Info: [ 49%] LOSS: training ≈ 0.2527
[ Info: [ 50%] LOSS: training ≈ 0.2527
[ Info: [ 50%] LOSS: training ≈ 0.2527
[ Info: [ 50%] LOSS: training ≈ 0.2527
[ Info: [ 51%] LOSS: training ≈ 0.2526
[ Info: [ 52%] LOSS: training ≈ 0.2526
[ Info: [ 52%] LOSS: training ≈ 0.2526
[ Info: [ 52%] LOSS: training ≈ 0.2526
[ Info: [ 53%] LOSS: training ≈ 0.2526
[ Info: [ 54%] LOSS: training ≈ 0.2526
[ Info: [ 54%] LOSS: training ≈ 0.2525
[ Info: [ 55%] LOSS: training ≈ 0.2525
[ Info: [ 55%] LOSS: training ≈ 0.2525
[ Info: [ 56%] LOSS: training ≈ 0.2525
[ Info: [ 56%] LOSS: training ≈ 0.2525
[ Info: [ 56%] LOSS: training ≈ 0.2525
[ Info: [ 57%] LOSS: training ≈ 0.2525
[ Info: [ 57%] LOSS: training ≈ 0.2525
[ Info: [ 58%] LOSS: training ≈ 0.2525
[ Info: [ 58%] LOSS: training ≈ 0.2525
[ Info: [ 59%] LOSS: training ≈ 0.2524
[ Info: [ 60%] LOSS: training ≈ 0.2524
[ Info: [ 60%] LOSS: training ≈ 0.2524
[ Info: [ 60%] LOSS: training ≈ 0.2524
[ Info: [ 61%] LOSS: training ≈ 0.2524
[ Info: [ 62%] LOSS: training ≈ 0.2524
[ Info: [ 62%] LOSS: training ≈ 0.2524
[ Info: [ 62%] LOSS: training ≈ 0.2524
[ Info: [ 63%] LOSS: training ≈ 0.2524
[ Info: [ 64%] LOSS: training ≈ 0.2524
[ Info: [ 64%] LOSS: training ≈ 0.2524
[ Info: [ 64%] LOSS: training ≈ 0.2524
[ Info: [ 65%] LOSS: training ≈ 0.2524
[ Info: [ 66%] LOSS: training ≈ 0.2523
[ Info: [ 66%] LOSS: training ≈ 0.2523
[ Info: [ 66%] LOSS: training ≈ 0.2523
[ Info: [ 67%] LOSS: training ≈ 0.2523
[ Info: [ 68%] LOSS: training ≈ 0.2523
[ Info: [ 68%] LOSS: training ≈ 0.2523
[ Info: [ 68%] LOSS: training ≈ 0.2523
[ Info: [ 69%] LOSS: training ≈ 0.2523
[ Info: [ 70%] LOSS: training ≈ 0.2523
[ Info: [ 70%] LOSS: training ≈ 0.2523
[ Info: [ 70%] LOSS: training ≈ 0.2523
[ Info: [ 71%] LOSS: training ≈ 0.2523
[ Info: [ 72%] LOSS: training ≈ 0.2523
[ Info: [ 72%] LOSS: training ≈ 0.2523
[ Info: [ 72%] LOSS: training ≈ 0.2523
[ Info: [ 73%] LOSS: training ≈ 0.2523
[ Info: [ 74%] LOSS: training ≈ 0.2523
[ Info: [ 74%] LOSS: training ≈ 0.2523
[ Info: [ 74%] LOSS: training ≈ 0.2523
[ Info: [ 75%] LOSS: training ≈ 0.2523
[ Info: [ 76%] LOSS: training ≈ 0.2523
[ Info: [ 76%] LOSS: training ≈ 0.2523
[ Info: [ 76%] LOSS: training ≈ 0.2523
[ Info: [ 77%] LOSS: training ≈ 0.2523
[ Info: [ 78%] LOSS: training ≈ 0.2523
[ Info: [ 78%] LOSS: training ≈ 0.2523
[ Info: [ 78%] LOSS: training ≈ 0.2522
[ Info: [ 79%] LOSS: training ≈ 0.2522
[ Info: [ 80%] LOSS: training ≈ 0.2522
[ Info: [ 80%] LOSS: training ≈ 0.2522
[ Info: [ 80%] LOSS: training ≈ 0.2522
[ Info: [ 81%] LOSS: training ≈ 0.2522
[ Info: [ 82%] LOSS: training ≈ 0.2522
[ Info: [ 82%] LOSS: training ≈ 0.2522
[ Info: [ 82%] LOSS: training ≈ 0.2522
[ Info: [ 83%] LOSS: training ≈ 0.2522
[ Info: [ 84%] LOSS: training ≈ 0.2522
[ Info: [ 84%] LOSS: training ≈ 0.2522
[ Info: [ 84%] LOSS: training ≈ 0.2522
[ Info: [ 85%] LOSS: training ≈ 0.2522
[ Info: [ 86%] LOSS: training ≈ 0.2522
[ Info: [ 86%] LOSS: training ≈ 0.2522
[ Info: [ 86%] LOSS: training ≈ 0.2522
[ Info: [ 87%] LOSS: training ≈ 0.2522
[ Info: [ 88%] LOSS: training ≈ 0.2522
[ Info: [ 88%] LOSS: training ≈ 0.2522
[ Info: [ 88%] LOSS: training ≈ 0.2522
[ Info: [ 89%] LOSS: training ≈ 0.2522
[ Info: [ 90%] LOSS: training ≈ 0.2522
[ Info: [ 90%] LOSS: training ≈ 0.2522
[ Info: [ 90%] LOSS: training ≈ 0.2522
[ Info: [ 91%] LOSS: training ≈ 0.2522
[ Info: [ 92%] LOSS: training ≈ 0.2522
[ Info: [ 92%] LOSS: training ≈ 0.2522
[ Info: [ 92%] LOSS: training ≈ 0.2522
[ Info: [ 93%] LOSS: training ≈ 0.2522
[ Info: [ 94%] LOSS: training ≈ 0.2522
[ Info: [ 94%] LOSS: training ≈ 0.2522
[ Info: [ 94%] LOSS: training ≈ 0.2522
[ Info: [ 95%] LOSS: training ≈ 0.2522
[ Info: [ 96%] LOSS: training ≈ 0.2522
[ Info: [ 96%] LOSS: training ≈ 0.2522
[ Info: [ 96%] LOSS: training ≈ 0.2522
[ Info: [ 97%] LOSS: training ≈ 0.2522
[ Info: [ 98%] LOSS: training ≈ 0.2522
[ Info: [ 98%] LOSS: training ≈ 0.2522
[ Info: [ 98%] LOSS: training ≈ 0.2522
[ Info: [ 99%] LOSS: training ≈ 0.2522
[ Info: [100%] LOSS: training ≈ 0.2522
[ Info: [100%] LOSS: training ≈ 0.2522
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:90
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:90
[ Info: [ 2 vars.] MCC val. ≈ -0.0
[ Info: [ 3 vars.] MCC val. ≈ 0.522
[ Info: [ 4 vars.] MCC val. ≈ 0.536
[ Info: [ 5 vars.] MCC val. ≈ 0.543
[ Info: Optimal var. pool: [1, 12, 19, 18, 15]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:44
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:44
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:90
[ Info: [ 0 vars.] MCC val. ≈ -0.0
[ Info: [ 1 vars.] MCC val. ≈ 0.78
[ Info: [ 2 vars.] MCC val. ≈ 0.821
[ Info: Optimal var. pool: [8, 3]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:44
[ Info: [19 vars.] MCC val. ≈ -0.0
[ Info: [18 vars.] MCC val. ≈ 0.501
[ Info: [17 vars.] MCC val. ≈ 0.779
[ Info: [16 vars.] MCC val. ≈ 0.793
[ Info: [15 vars.] MCC val. ≈ 0.8
[ Info: Optimal var. pool: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 15, 16, 17, 18]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:44
[ Info: [ 9 vars.] MCC val. ≈ -0.0
[ Info: [ 8 vars.] MCC val. ≈ 0.724
[ Info: [ 7 vars.] MCC val. ≈ 0.731
[ Info: [ 6 vars.] MCC val. ≈ 0.738
[ Info: Optimal var. pool: [1, 3, 5, 6, 7, 9]
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:90
[ Info: [ 2 vars.] MCC val. ≈ -0.0
[ Info: [ 3 vars.] MCC val. ≈ 0.516
[ Info: Optimal var. pool: [12, 13, 1]
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/selection.jl:90
[ Info: [ 0 vars.] MCC val. ≈ -0.0
[ Info: [ 1 vars.] MCC val. ≈ 0.725
[ Info: [ 2 vars.] MCC val. ≈ 0.738
[ Info: Optimal var. pool: [8, 7]
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/S5gCZ/src/variables/vif.jl:24
Test Summary: | Pass  Total      Time
Package       |  300    300  17m23.0s
     Testing SDeMo tests passed 

Testing completed after 1106.94s

PkgEval succeeded after 1151.37s