Package evaluation of SDeMo on Julia 1.13.0-DEV.582 (c0a1728d50*) started at 2025-05-14T13:12:38.137 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 8.48s ################################################################################ # 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 v0.9.4 [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 v1.8.0 [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 v1.7.0 [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 v2025.2.25 [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 3.89s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 28.11s ################################################################################ # Testing # Testing SDeMo Status `/tmp/jl_ABIIqq/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_ABIIqq/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 v0.9.4 [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 v1.8.0 [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 v1.7.0 [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 v2025.2.25 [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... Precompiling packages... 1708.4 ms ✓ Arpack_jll 1582.5 ms ✓ Arpack 4892.7 ms ✓ MultivariateStats Info Given SDeMo was explicitly requested, output will be shown live  WARNING: Method definition kwcall(NamedTuple{names, T} where T<:Tuple where names, typeof(Compat.get_num_threads), Any...) in module CompatLinearAlgebraExt at deprecated.jl:223 overwritten in module CompatLinearAlgebraExt on the same line (check for duplicate calls to `include`). ERROR: Method overwriting is not permitted during Module precompilation. Use `__precompile__(false)` to opt-out of precompilation. 8754.4 ms ? SDeMo 3 dependencies successfully precompiled in 19 seconds. 68 already precompiled. 1 dependencies failed but may be precompilable after restarting julia 1 dependency had output during precompilation: ┌ SDeMo │ [Output was shown above] └ Precompiling packages... 3984.8 ms ✓ Distributions → DistributionsTestExt 1 dependency successfully precompiled in 4 seconds. 49 already precompiled. [ Info: [ 0%] LOSS: training ≈ 0.4986 validation ≈ 0.4945 ( 99%) [ Info: [ 1%] LOSS: training ≈ 0.4218 validation ≈ 0.43 (102%) [ Info: [ 2%] LOSS: training ≈ 0.3838 validation ≈ 0.399 (104%) [ Info: [ 2%] LOSS: training ≈ 0.3613 validation ≈ 0.3809 (105%) [ Info: [ 2%] LOSS: training ≈ 0.3465 validation ≈ 0.369 (107%) [ Info: [ 3%] LOSS: training ≈ 0.3359 validation ≈ 0.3604 (107%) [ Info: [ 4%] LOSS: training ≈ 0.3278 validation ≈ 0.3538 (108%) [ Info: [ 4%] LOSS: training ≈ 0.3215 validation ≈ 0.3485 (108%) [ Info: [ 4%] LOSS: training ≈ 0.3164 validation ≈ 0.344 (109%) [ Info: [ 5%] LOSS: training ≈ 0.312 validation ≈ 0.3402 (109%) [ Info: [ 6%] LOSS: training ≈ 0.3084 validation ≈ 0.3368 (109%) [ Info: [ 6%] LOSS: training ≈ 0.3052 validation ≈ 0.3339 (109%) [ Info: [ 6%] LOSS: training ≈ 0.3023 validation ≈ 0.3312 (110%) [ Info: [ 7%] LOSS: training ≈ 0.2998 validation ≈ 0.3288 (110%) [ Info: [ 8%] LOSS: training ≈ 0.2976 validation ≈ 0.3266 (110%) [ Info: [ 8%] LOSS: training ≈ 0.2955 validation ≈ 0.3245 (110%) [ Info: [ 8%] LOSS: training ≈ 0.2936 validation ≈ 0.3227 (110%) [ Info: [ 9%] LOSS: training ≈ 0.2919 validation ≈ 0.3209 (110%) [ Info: [ 10%] LOSS: training ≈ 0.2903 validation ≈ 0.3192 (110%) [ Info: [ 10%] LOSS: training ≈ 0.2888 validation ≈ 0.3177 (110%) [ Info: [ 10%] LOSS: training ≈ 0.2875 validation ≈ 0.3163 (110%) [ Info: [ 11%] LOSS: training ≈ 0.2862 validation ≈ 0.3149 (110%) [ Info: [ 12%] LOSS: training ≈ 0.2849 validation ≈ 0.3136 (110%) [ Info: [ 12%] LOSS: training ≈ 0.2838 validation ≈ 0.3124 (110%) [ Info: [ 12%] LOSS: training ≈ 0.2827 validation ≈ 0.3112 (110%) [ Info: [ 13%] LOSS: training ≈ 0.2817 validation ≈ 0.3101 (110%) [ Info: [ 14%] LOSS: training ≈ 0.2807 validation ≈ 0.309 (110%) [ Info: [ 14%] LOSS: training ≈ 0.2798 validation ≈ 0.308 (110%) [ Info: [ 14%] LOSS: training ≈ 0.2789 validation ≈ 0.307 (110%) [ Info: [ 15%] LOSS: training ≈ 0.2781 validation ≈ 0.3061 (110%) [ Info: [ 16%] LOSS: training ≈ 0.2773 validation ≈ 0.3052 (110%) [ Info: [ 16%] LOSS: training ≈ 0.2765 validation ≈ 0.3044 (110%) [ Info: [ 16%] LOSS: training ≈ 0.2758 validation ≈ 0.3035 (110%) [ Info: [ 17%] LOSS: training ≈ 0.2751 validation ≈ 0.3028 (110%) [ Info: [ 18%] LOSS: training ≈ 0.2744 validation ≈ 0.302 (110%) [ Info: [ 18%] LOSS: training ≈ 0.2737 validation ≈ 0.3013 (110%) [ Info: [ 18%] LOSS: training ≈ 0.2731 validation ≈ 0.3005 (110%) [ Info: [ 19%] LOSS: training ≈ 0.2725 validation ≈ 0.2999 (110%) [ Info: [ 20%] LOSS: training ≈ 0.2719 validation ≈ 0.2992 (110%) [ Info: [ 20%] LOSS: training ≈ 0.2714 validation ≈ 0.2985 (110%) [ Info: [ 20%] LOSS: training ≈ 0.2708 validation ≈ 0.2979 (110%) [ Info: [ 21%] LOSS: training ≈ 0.2703 validation ≈ 0.2973 (110%) [ Info: [ 22%] LOSS: training ≈ 0.2698 validation ≈ 0.2967 (110%) [ Info: [ 22%] LOSS: training ≈ 0.2693 validation ≈ 0.2962 (110%) [ Info: [ 22%] LOSS: training ≈ 0.2689 validation ≈ 0.2956 (110%) [ Info: [ 23%] LOSS: training ≈ 0.2684 validation ≈ 0.2951 (110%) [ Info: [ 24%] LOSS: training ≈ 0.268 validation ≈ 0.2946 (110%) [ Info: [ 24%] LOSS: training ≈ 0.2676 validation ≈ 0.294 (110%) [ Info: [ 24%] LOSS: training ≈ 0.2672 validation ≈ 0.2936 (110%) [ Info: [ 25%] LOSS: training ≈ 0.2668 validation ≈ 0.2931 (110%) [ Info: [ 26%] LOSS: training ≈ 0.2664 validation ≈ 0.2926 (110%) [ Info: [ 26%] LOSS: training ≈ 0.266 validation ≈ 0.2922 (110%) [ Info: [ 26%] LOSS: training ≈ 0.2656 validation ≈ 0.2917 (110%) [ Info: [ 27%] LOSS: training ≈ 0.2653 validation ≈ 0.2913 (110%) [ Info: [ 28%] LOSS: training ≈ 0.265 validation ≈ 0.2909 (110%) [ Info: [ 28%] LOSS: training ≈ 0.2646 validation ≈ 0.2905 (110%) [ Info: [ 28%] LOSS: training ≈ 0.2643 validation ≈ 0.2901 (110%) [ Info: [ 29%] LOSS: training ≈ 0.264 validation ≈ 0.2897 (110%) [ Info: [ 30%] LOSS: training ≈ 0.2637 validation ≈ 0.2893 (110%) [ Info: [ 30%] LOSS: training ≈ 0.2634 validation ≈ 0.2889 (110%) [ Info: [ 30%] LOSS: training ≈ 0.2631 validation ≈ 0.2886 (110%) [ Info: [ 31%] LOSS: training ≈ 0.2628 validation ≈ 0.2882 (110%) [ Info: [ 32%] LOSS: training ≈ 0.2626 validation ≈ 0.2879 (110%) [ Info: [ 32%] LOSS: training ≈ 0.2623 validation ≈ 0.2875 (110%) [ Info: [ 32%] LOSS: training ≈ 0.2621 validation ≈ 0.2872 (110%) [ Info: [ 33%] LOSS: training ≈ 0.2618 validation ≈ 0.2869 (110%) [ Info: [ 34%] LOSS: training ≈ 0.2616 validation ≈ 0.2866 (110%) [ Info: [ 34%] LOSS: training ≈ 0.2613 validation ≈ 0.2863 (110%) [ Info: [ 34%] LOSS: training ≈ 0.2611 validation ≈ 0.286 (110%) [ Info: [ 35%] LOSS: training ≈ 0.2609 validation ≈ 0.2857 (110%) [ Info: [ 36%] LOSS: training ≈ 0.2607 validation ≈ 0.2854 (109%) [ Info: [ 36%] LOSS: training ≈ 0.2605 validation ≈ 0.2851 (109%) [ Info: [ 36%] LOSS: training ≈ 0.2603 validation ≈ 0.2848 (109%) [ Info: [ 37%] LOSS: training ≈ 0.2601 validation ≈ 0.2846 (109%) [ Info: [ 38%] LOSS: training ≈ 0.2599 validation ≈ 0.2843 (109%) [ Info: [ 38%] LOSS: training ≈ 0.2597 validation ≈ 0.2841 (109%) [ Info: [ 38%] LOSS: training ≈ 0.2595 validation ≈ 0.2838 (109%) [ Info: [ 39%] LOSS: training ≈ 0.2593 validation ≈ 0.2836 (109%) [ Info: [ 40%] LOSS: training ≈ 0.2591 validation ≈ 0.2833 (109%) [ Info: [ 40%] LOSS: training ≈ 0.259 validation ≈ 0.2831 (109%) [ Info: [ 40%] LOSS: training ≈ 0.2588 validation ≈ 0.2829 (109%) [ Info: [ 41%] LOSS: training ≈ 0.2586 validation ≈ 0.2826 (109%) [ Info: [ 42%] LOSS: training ≈ 0.2585 validation ≈ 0.2824 (109%) [ Info: [ 42%] LOSS: training ≈ 0.2583 validation ≈ 0.2822 (109%) [ Info: [ 42%] LOSS: training ≈ 0.2582 validation ≈ 0.282 (109%) [ Info: [ 43%] LOSS: training ≈ 0.258 validation ≈ 0.2818 (109%) [ Info: [ 44%] LOSS: training ≈ 0.2579 validation ≈ 0.2816 (109%) [ Info: [ 44%] LOSS: training ≈ 0.2577 validation ≈ 0.2814 (109%) [ Info: [ 44%] LOSS: training ≈ 0.2576 validation ≈ 0.2812 (109%) [ Info: [ 45%] LOSS: training ≈ 0.2575 validation ≈ 0.281 (109%) [ Info: [ 46%] LOSS: training ≈ 0.2573 validation ≈ 0.2808 (109%) [ Info: [ 46%] LOSS: training ≈ 0.2572 validation ≈ 0.2806 (109%) [ Info: [ 46%] LOSS: training ≈ 0.2571 validation ≈ 0.2804 (109%) [ Info: [ 47%] LOSS: training ≈ 0.257 validation ≈ 0.2802 (109%) [ Info: [ 48%] LOSS: training ≈ 0.2569 validation ≈ 0.2801 (109%) [ Info: [ 48%] LOSS: training ≈ 0.2567 validation ≈ 0.2799 (109%) [ Info: [ 48%] LOSS: training ≈ 0.2566 validation ≈ 0.2797 (109%) [ Info: [ 49%] LOSS: training ≈ 0.2565 validation ≈ 0.2796 (109%) [ Info: [ 50%] LOSS: training ≈ 0.2564 validation ≈ 0.2794 (109%) [ Info: [ 50%] LOSS: training ≈ 0.2563 validation ≈ 0.2792 (109%) [ Info: [ 50%] LOSS: training ≈ 0.2562 validation ≈ 0.2791 (109%) [ Info: [ 51%] LOSS: training ≈ 0.2561 validation ≈ 0.2789 (109%) [ Info: [ 52%] LOSS: training ≈ 0.256 validation ≈ 0.2788 (109%) [ Info: [ 52%] LOSS: training ≈ 0.2559 validation ≈ 0.2786 (109%) [ Info: [ 52%] LOSS: training ≈ 0.2558 validation ≈ 0.2785 (109%) [ Info: [ 53%] LOSS: training ≈ 0.2557 validation ≈ 0.2783 (109%) [ Info: [ 54%] LOSS: training ≈ 0.2556 validation ≈ 0.2782 (109%) [ Info: [ 54%] LOSS: training ≈ 0.2555 validation ≈ 0.2781 (109%) [ Info: [ 55%] LOSS: training ≈ 0.2554 validation ≈ 0.2779 (109%) [ Info: [ 55%] LOSS: training ≈ 0.2553 validation ≈ 0.2778 (109%) [ Info: [ 56%] LOSS: training ≈ 0.2553 validation ≈ 0.2777 (109%) [ Info: [ 56%] LOSS: training ≈ 0.2552 validation ≈ 0.2775 (109%) [ Info: [ 56%] LOSS: training ≈ 0.2551 validation ≈ 0.2774 (109%) [ Info: [ 57%] LOSS: training ≈ 0.255 validation ≈ 0.2773 (109%) [ Info: [ 57%] LOSS: training ≈ 0.2549 validation ≈ 0.2772 (109%) [ Info: [ 58%] LOSS: training ≈ 0.2549 validation ≈ 0.277 (109%) [ Info: [ 58%] LOSS: training ≈ 0.2548 validation ≈ 0.2769 (109%) [ Info: [ 59%] LOSS: training ≈ 0.2547 validation ≈ 0.2768 (109%) [ Info: [ 60%] LOSS: training ≈ 0.2547 validation ≈ 0.2767 (109%) [ Info: [ 60%] LOSS: training ≈ 0.2546 validation ≈ 0.2766 (109%) [ Info: [ 60%] LOSS: training ≈ 0.2545 validation ≈ 0.2765 (109%) [ Info: [ 61%] LOSS: training ≈ 0.2544 validation ≈ 0.2764 (109%) [ Info: [ 62%] LOSS: training ≈ 0.2544 validation ≈ 0.2762 (109%) [ Info: [ 62%] LOSS: training ≈ 0.2543 validation ≈ 0.2761 (109%) [ Info: [ 62%] LOSS: training ≈ 0.2543 validation ≈ 0.276 (109%) [ Info: [ 63%] LOSS: training ≈ 0.2542 validation ≈ 0.2759 (109%) [ Info: [ 64%] LOSS: training ≈ 0.2541 validation ≈ 0.2758 (109%) [ Info: [ 64%] LOSS: training ≈ 0.2541 validation ≈ 0.2757 (109%) [ Info: [ 64%] LOSS: training ≈ 0.254 validation ≈ 0.2756 (109%) [ Info: [ 65%] LOSS: training ≈ 0.254 validation ≈ 0.2755 (108%) [ Info: [ 66%] LOSS: training ≈ 0.2539 validation ≈ 0.2754 (108%) [ Info: [ 66%] LOSS: training ≈ 0.2538 validation ≈ 0.2753 (108%) [ Info: [ 66%] LOSS: training ≈ 0.2538 validation ≈ 0.2753 (108%) [ Info: [ 67%] LOSS: training ≈ 0.2537 validation ≈ 0.2752 (108%) [ Info: [ 68%] LOSS: training ≈ 0.2537 validation ≈ 0.2751 (108%) [ Info: [ 68%] LOSS: training ≈ 0.2536 validation ≈ 0.275 (108%) [ Info: [ 68%] LOSS: training ≈ 0.2536 validation ≈ 0.2749 (108%) [ Info: [ 69%] LOSS: training ≈ 0.2535 validation ≈ 0.2748 (108%) [ Info: [ 70%] LOSS: training ≈ 0.2535 validation ≈ 0.2747 (108%) [ Info: [ 70%] LOSS: training ≈ 0.2534 validation ≈ 0.2746 (108%) [ Info: [ 70%] LOSS: training ≈ 0.2534 validation ≈ 0.2746 (108%) [ Info: [ 71%] LOSS: training ≈ 0.2533 validation ≈ 0.2745 (108%) [ Info: [ 72%] LOSS: training ≈ 0.2533 validation ≈ 0.2744 (108%) [ Info: [ 72%] LOSS: training ≈ 0.2533 validation ≈ 0.2743 (108%) [ Info: [ 72%] LOSS: training ≈ 0.2532 validation ≈ 0.2743 (108%) [ Info: [ 73%] LOSS: training ≈ 0.2532 validation ≈ 0.2742 (108%) [ Info: [ 74%] LOSS: training ≈ 0.2531 validation ≈ 0.2741 (108%) [ Info: [ 74%] LOSS: training ≈ 0.2531 validation ≈ 0.274 (108%) [ Info: [ 74%] LOSS: training ≈ 0.253 validation ≈ 0.274 (108%) [ Info: [ 75%] LOSS: training ≈ 0.253 validation ≈ 0.2739 (108%) [ Info: [ 76%] LOSS: training ≈ 0.253 validation ≈ 0.2738 (108%) [ Info: [ 76%] LOSS: training ≈ 0.2529 validation ≈ 0.2737 (108%) [ Info: [ 76%] LOSS: training ≈ 0.2529 validation ≈ 0.2737 (108%) [ Info: [ 77%] LOSS: training ≈ 0.2529 validation ≈ 0.2736 (108%) [ Info: [ 78%] LOSS: training ≈ 0.2528 validation ≈ 0.2735 (108%) [ Info: [ 78%] LOSS: training ≈ 0.2528 validation ≈ 0.2735 (108%) [ Info: [ 78%] LOSS: training ≈ 0.2527 validation ≈ 0.2734 (108%) [ Info: [ 79%] LOSS: training ≈ 0.2527 validation ≈ 0.2733 (108%) [ Info: [ 80%] LOSS: training ≈ 0.2527 validation ≈ 0.2733 (108%) [ Info: [ 80%] LOSS: training ≈ 0.2526 validation ≈ 0.2732 (108%) [ Info: [ 80%] LOSS: training ≈ 0.2526 validation ≈ 0.2731 (108%) [ Info: [ 81%] LOSS: training ≈ 0.2526 validation ≈ 0.2731 (108%) [ Info: [ 82%] LOSS: training ≈ 0.2525 validation ≈ 0.273 (108%) [ Info: [ 82%] LOSS: training ≈ 0.2525 validation ≈ 0.273 (108%) [ Info: [ 82%] LOSS: training ≈ 0.2525 validation ≈ 0.2729 (108%) [ Info: [ 83%] LOSS: training ≈ 0.2525 validation ≈ 0.2729 (108%) [ Info: [ 84%] LOSS: training ≈ 0.2524 validation ≈ 0.2728 (108%) [ Info: [ 84%] LOSS: training ≈ 0.2524 validation ≈ 0.2727 (108%) [ Info: [ 84%] LOSS: training ≈ 0.2524 validation ≈ 0.2727 (108%) [ Info: [ 85%] LOSS: training ≈ 0.2523 validation ≈ 0.2726 (108%) [ Info: [ 86%] LOSS: training ≈ 0.2523 validation ≈ 0.2726 (108%) [ Info: [ 86%] LOSS: training ≈ 0.2523 validation ≈ 0.2725 (108%) [ Info: [ 86%] LOSS: training ≈ 0.2523 validation ≈ 0.2725 (108%) [ Info: [ 87%] LOSS: training ≈ 0.2522 validation ≈ 0.2724 (108%) [ Info: [ 88%] LOSS: training ≈ 0.2522 validation ≈ 0.2724 (108%) [ Info: [ 88%] LOSS: training ≈ 0.2522 validation ≈ 0.2723 (108%) [ Info: [ 88%] LOSS: training ≈ 0.2522 validation ≈ 0.2723 (108%) [ Info: [ 89%] LOSS: training ≈ 0.2521 validation ≈ 0.2722 (108%) [ Info: [ 90%] LOSS: training ≈ 0.2521 validation ≈ 0.2722 (108%) [ Info: [ 90%] LOSS: training ≈ 0.2521 validation ≈ 0.2721 (108%) [ Info: [ 90%] LOSS: training ≈ 0.2521 validation ≈ 0.2721 (108%) [ Info: [ 91%] LOSS: training ≈ 0.252 validation ≈ 0.272 (108%) [ Info: [ 92%] LOSS: training ≈ 0.252 validation ≈ 0.272 (108%) [ Info: [ 92%] LOSS: training ≈ 0.252 validation ≈ 0.2719 (108%) [ Info: [ 92%] LOSS: training ≈ 0.252 validation ≈ 0.2719 (108%) [ Info: [ 93%] LOSS: training ≈ 0.2519 validation ≈ 0.2718 (108%) [ Info: [ 94%] LOSS: training ≈ 0.2519 validation ≈ 0.2718 (108%) [ Info: [ 94%] LOSS: training ≈ 0.2519 validation ≈ 0.2717 (108%) [ Info: [ 94%] LOSS: training ≈ 0.2519 validation ≈ 0.2717 (108%) [ Info: [ 95%] LOSS: training ≈ 0.2519 validation ≈ 0.2717 (108%) [ Info: [ 96%] LOSS: training ≈ 0.2518 validation ≈ 0.2716 (108%) [ Info: [ 96%] LOSS: training ≈ 0.2518 validation ≈ 0.2716 (108%) [ Info: [ 96%] LOSS: training ≈ 0.2518 validation ≈ 0.2715 (108%) [ Info: [ 97%] LOSS: training ≈ 0.2518 validation ≈ 0.2715 (108%) [ Info: [ 98%] LOSS: training ≈ 0.2518 validation ≈ 0.2714 (108%) [ Info: [ 98%] LOSS: training ≈ 0.2517 validation ≈ 0.2714 (108%) [ Info: [ 98%] LOSS: training ≈ 0.2517 validation ≈ 0.2714 (108%) [ Info: [ 99%] LOSS: training ≈ 0.2517 validation ≈ 0.2713 (108%) [ Info: [100%] LOSS: training ≈ 0.2517 validation ≈ 0.2713 (108%) [ Info: [100%] LOSS: training ≈ 0.2517 validation ≈ 0.2712 (108%) [ 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. ≈ 0.487 [ Info: Optimal var. pool: [1, 12, 2] ┌ 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. ≈ 0.814 [ Info: [ 2 vars.] MCC val. ≈ 0.828 [ Info: Optimal var. pool: [8, 3] ┌ 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. ≈ 0.536 [ Info: [17 vars.] MCC val. ≈ 0.772 [ Info: [16 vars.] MCC val. ≈ 0.786 [ Info: Optimal var. pool: [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18] ┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead └ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:44 [ Info: [ 9 vars.] MCC val. ≈ -0.0 [ Info: [ 8 vars.] MCC val. ≈ 0.765 [ Info: [ 7 vars.] MCC val. ≈ 0.773 [ Info: [ 6 vars.] MCC val. ≈ 0.786 [ Info: [ 5 vars.] MCC val. ≈ 0.8 [ Info: [ 4 vars.] MCC val. ≈ 0.807 [ Info: Optimal var. pool: [2, 3, 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. ≈ 0.468 [ 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. ≈ 0.808 [ Info: [ 2 vars.] MCC val. ≈ 0.828 [ Info: Optimal var. pool: [5, 7] [ Info: Baseline mcc: -2.8367742685852565e-17 [ Info: Optimal 1 variables model - mcc ≈ 0.7392 [ Info: Optimal 2 variables model - mcc ≈ 0.7583 [ Info: Optimal 3 variables model - mcc ≈ 0.7647 [ Info: Returning model with 4 variables - mcc ≈ 0.7647 Test Summary: | Pass Total Time Package | 294 294 24m52.0s Testing SDeMo tests passed Testing completed after 1547.1s PkgEval succeeded after 1609.99s