Package evaluation of SDeMo on Julia 1.13.0-DEV.860 (6ddb3d6410*) started at 2025-07-13T16:53:37.104 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 9.17s ################################################################################ # Installation # Installing SDeMo... Resolving package versions... Updating `~/.julia/environments/v1.13/Project.toml` [3e5feb82] + SDeMo v1.5.0 Updating `~/.julia/environments/v1.13/Manifest.toml` [66dad0bd] + AliasTables v1.1.3 [7d9fca2a] + Arpack v0.5.4 [34da2185] + Compat v4.17.0 [9a962f9c] + DataAPI v1.16.0 [864edb3b] + DataStructures v0.18.22 [31c24e10] + Distributions v0.25.120 [ffbed154] + DocStringExtensions v0.9.5 [1a297f60] + FillArrays v1.13.0 [34004b35] + HypergeometricFunctions v0.3.28 [92d709cd] + IrrationalConstants v0.2.4 [692b3bcd] + JLLWrappers v1.7.0 [682c06a0] + JSON v0.21.4 [2ab3a3ac] + LogExpFunctions v0.3.29 [e1d29d7a] + Missings v1.2.0 [6f286f6a] + MultivariateStats v0.10.3 [bac558e1] + OrderedCollections v1.8.1 [90014a1f] + PDMats v0.11.35 [69de0a69] + Parsers v2.8.3 [aea7be01] + PrecompileTools v1.3.2 [21216c6a] + Preferences v1.4.3 [43287f4e] + PtrArrays v1.3.0 [1fd47b50] + QuadGK v2.11.2 [189a3867] + Reexport v1.2.2 [79098fc4] + Rmath v0.8.0 [3e5feb82] + SDeMo v1.5.0 [a2af1166] + SortingAlgorithms v1.2.1 [276daf66] + SpecialFunctions v2.5.1 [10745b16] + Statistics v1.11.1 [82ae8749] + StatsAPI v1.7.1 [2913bbd2] + StatsBase v0.34.5 [4c63d2b9] + StatsFuns v1.5.0 [1c621080] + TestItems v1.0.0 ⌅ [68821587] + Arpack_jll v3.5.1+1 [efe28fd5] + OpenSpecFun_jll v0.5.6+0 [f50d1b31] + Rmath_jll v0.5.1+0 [0dad84c5] + ArgTools v1.1.2 [56f22d72] + Artifacts v1.11.0 [2a0f44e3] + Base64 v1.11.0 [ade2ca70] + Dates v1.11.0 [f43a241f] + Downloads v1.7.0 [7b1f6079] + FileWatching v1.11.0 [b77e0a4c] + InteractiveUtils v1.11.0 [ac6e5ff7] + JuliaSyntaxHighlighting v1.12.0 [b27032c2] + LibCURL v0.6.4 [76f85450] + LibGit2 v1.11.0 [8f399da3] + Libdl v1.11.0 [37e2e46d] + LinearAlgebra v1.12.0 [56ddb016] + Logging v1.11.0 [d6f4376e] + Markdown v1.11.0 [a63ad114] + Mmap v1.11.0 [ca575930] + NetworkOptions v1.3.0 [44cfe95a] + Pkg v1.13.0 [de0858da] + Printf v1.11.0 [9a3f8284] + Random v1.11.0 [ea8e919c] + SHA v0.7.0 [9e88b42a] + Serialization v1.11.0 [2f01184e] + SparseArrays v1.12.0 [f489334b] + StyledStrings v1.11.0 [4607b0f0] + SuiteSparse [fa267f1f] + TOML v1.0.3 [a4e569a6] + Tar v1.10.0 [cf7118a7] + UUIDs v1.11.0 [4ec0a83e] + Unicode v1.11.0 [e66e0078] + CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] + LibCURL_jll v8.14.1+1 [e37daf67] + LibGit2_jll v1.9.1+0 [29816b5a] + LibSSH2_jll v1.11.3+1 [14a3606d] + MozillaCACerts_jll v2025.5.20 [4536629a] + OpenBLAS_jll v0.3.29+0 [05823500] + OpenLibm_jll v0.8.5+0 [458c3c95] + OpenSSL_jll v3.5.1+0 [efcefdf7] + PCRE2_jll v10.45.0+0 [bea87d4a] + SuiteSparse_jll v7.10.1+0 [83775a58] + Zlib_jll v1.3.1+2 [8e850b90] + libblastrampoline_jll v5.13.1+0 [8e850ede] + nghttp2_jll v1.65.0+0 [3f19e933] + p7zip_jll v17.5.0+2 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m` Installation completed after 4.46s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 47.84s ################################################################################ # Testing # Testing SDeMo Status `/tmp/jl_20vTDU/Project.toml` [3e5feb82] SDeMo v1.5.0 [10745b16] Statistics v1.11.1 [f8b46487] TestItemRunner v1.1.0 [8dfed614] Test v1.11.0 Status `/tmp/jl_20vTDU/Manifest.toml` [66dad0bd] AliasTables v1.1.3 [7d9fca2a] Arpack v0.5.4 [34da2185] Compat v4.17.0 [9a962f9c] DataAPI v1.16.0 [864edb3b] DataStructures v0.18.22 [31c24e10] Distributions v0.25.120 [ffbed154] DocStringExtensions v0.9.5 [1a297f60] FillArrays v1.13.0 [34004b35] HypergeometricFunctions v0.3.28 [92d709cd] IrrationalConstants v0.2.4 [692b3bcd] JLLWrappers v1.7.0 [682c06a0] JSON v0.21.4 [2ab3a3ac] LogExpFunctions v0.3.29 [e1d29d7a] Missings v1.2.0 [6f286f6a] MultivariateStats v0.10.3 [bac558e1] OrderedCollections v1.8.1 [90014a1f] PDMats v0.11.35 [69de0a69] Parsers v2.8.3 [aea7be01] PrecompileTools v1.3.2 [21216c6a] Preferences v1.4.3 [43287f4e] PtrArrays v1.3.0 [1fd47b50] QuadGK v2.11.2 [189a3867] Reexport v1.2.2 [79098fc4] Rmath v0.8.0 [3e5feb82] SDeMo v1.5.0 [a2af1166] SortingAlgorithms v1.2.1 [276daf66] SpecialFunctions v2.5.1 [10745b16] Statistics v1.11.1 [82ae8749] StatsAPI v1.7.1 [2913bbd2] StatsBase v0.34.5 [4c63d2b9] StatsFuns v1.5.0 [f8b46487] TestItemRunner v1.1.0 [1c621080] TestItems v1.0.0 ⌅ [68821587] Arpack_jll v3.5.1+1 [efe28fd5] OpenSpecFun_jll v0.5.6+0 [f50d1b31] Rmath_jll v0.5.1+0 [0dad84c5] ArgTools v1.1.2 [56f22d72] Artifacts v1.11.0 [2a0f44e3] Base64 v1.11.0 [ade2ca70] Dates v1.11.0 [f43a241f] Downloads v1.7.0 [7b1f6079] FileWatching v1.11.0 [b77e0a4c] InteractiveUtils v1.11.0 [ac6e5ff7] JuliaSyntaxHighlighting v1.12.0 [b27032c2] LibCURL v0.6.4 [76f85450] LibGit2 v1.11.0 [8f399da3] Libdl v1.11.0 [37e2e46d] LinearAlgebra v1.12.0 [56ddb016] Logging v1.11.0 [d6f4376e] Markdown v1.11.0 [a63ad114] Mmap v1.11.0 [ca575930] NetworkOptions v1.3.0 [44cfe95a] Pkg v1.13.0 [de0858da] Printf v1.11.0 [9a3f8284] Random v1.11.0 [ea8e919c] SHA v0.7.0 [9e88b42a] Serialization v1.11.0 [2f01184e] SparseArrays v1.12.0 [f489334b] StyledStrings v1.11.0 [4607b0f0] SuiteSparse [fa267f1f] TOML v1.0.3 [a4e569a6] Tar v1.10.0 [8dfed614] Test v1.11.0 [cf7118a7] UUIDs v1.11.0 [4ec0a83e] Unicode v1.11.0 [e66e0078] CompilerSupportLibraries_jll v1.3.0+1 [deac9b47] LibCURL_jll v8.14.1+1 [e37daf67] LibGit2_jll v1.9.1+0 [29816b5a] LibSSH2_jll v1.11.3+1 [14a3606d] MozillaCACerts_jll v2025.5.20 [4536629a] OpenBLAS_jll v0.3.29+0 [05823500] OpenLibm_jll v0.8.5+0 [458c3c95] OpenSSL_jll v3.5.1+0 [efcefdf7] PCRE2_jll v10.45.0+0 [bea87d4a] SuiteSparse_jll v7.10.1+0 [83775a58] Zlib_jll v1.3.1+2 [8e850b90] libblastrampoline_jll v5.13.1+0 [8e850ede] nghttp2_jll v1.65.0+0 [3f19e933] p7zip_jll v17.5.0+2 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. Testing Running tests... Precompiling packages... 18457.3 ms ✓ SDeMo 1 dependency successfully precompiled in 20 seconds. 72 already precompiled. Precompiling packages... 4865.1 ms ✓ Distributions → DistributionsTestExt 1 dependency successfully precompiled in 6 seconds. 49 already precompiled. ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 [ Info: Baseline mcc: -2.8367742685852565e-17 [ Info: Optimal 1 variables model - mcc ≈ 0.7454 [ Info: Optimal 2 variables model - mcc ≈ 0.775 [ Info: Returning model with 2 variables - mcc ≈ 0.775 [ Info: [ 0%] LOSS: training ≈ 0.5063 validation ≈ 0.4788 ( 95%) [ Info: [ 1%] LOSS: training ≈ 0.4339 validation ≈ 0.3999 ( 92%) [ Info: [ 2%] LOSS: training ≈ 0.3983 validation ≈ 0.3585 ( 90%) [ Info: [ 2%] LOSS: training ≈ 0.3772 validation ≈ 0.3328 ( 88%) [ Info: [ 2%] LOSS: training ≈ 0.3631 validation ≈ 0.3152 ( 87%) [ Info: [ 3%] LOSS: training ≈ 0.353 validation ≈ 0.3023 ( 86%) [ Info: [ 4%] LOSS: training ≈ 0.3453 validation ≈ 0.2924 ( 85%) [ Info: [ 4%] LOSS: training ≈ 0.3392 validation ≈ 0.2844 ( 84%) [ Info: [ 4%] LOSS: training ≈ 0.3342 validation ≈ 0.2779 ( 83%) [ Info: [ 5%] LOSS: training ≈ 0.33 validation ≈ 0.2724 ( 83%) [ Info: [ 6%] LOSS: training ≈ 0.3264 validation ≈ 0.2676 ( 82%) [ Info: [ 6%] LOSS: training ≈ 0.3233 validation ≈ 0.2635 ( 82%) [ Info: [ 6%] LOSS: training ≈ 0.3205 validation ≈ 0.26 ( 81%) [ Info: [ 7%] LOSS: training ≈ 0.318 validation ≈ 0.2568 ( 81%) [ Info: [ 8%] LOSS: training ≈ 0.3157 validation ≈ 0.2539 ( 80%) [ Info: [ 8%] LOSS: training ≈ 0.3136 validation ≈ 0.2513 ( 80%) [ Info: [ 8%] LOSS: training ≈ 0.3118 validation ≈ 0.249 ( 80%) [ Info: [ 9%] LOSS: training ≈ 0.31 validation ≈ 0.2469 ( 80%) [ Info: [ 10%] LOSS: training ≈ 0.3084 validation ≈ 0.2449 ( 79%) [ Info: [ 10%] LOSS: training ≈ 0.3069 validation ≈ 0.2431 ( 79%) [ Info: [ 10%] LOSS: training ≈ 0.3055 validation ≈ 0.2415 ( 79%) [ Info: [ 11%] LOSS: training ≈ 0.3042 validation ≈ 0.2399 ( 79%) [ Info: [ 12%] LOSS: training ≈ 0.3029 validation ≈ 0.2385 ( 79%) [ Info: [ 12%] LOSS: training ≈ 0.3018 validation ≈ 0.2371 ( 79%) [ Info: [ 12%] LOSS: training ≈ 0.3006 validation ≈ 0.2359 ( 78%) [ Info: [ 13%] LOSS: training ≈ 0.2996 validation ≈ 0.2347 ( 78%) [ Info: [ 14%] LOSS: training ≈ 0.2986 validation ≈ 0.2336 ( 78%) [ Info: [ 14%] LOSS: training ≈ 0.2976 validation ≈ 0.2325 ( 78%) [ Info: [ 14%] LOSS: training ≈ 0.2967 validation ≈ 0.2315 ( 78%) [ Info: [ 15%] LOSS: training ≈ 0.2958 validation ≈ 0.2306 ( 78%) [ Info: [ 16%] LOSS: training ≈ 0.295 validation ≈ 0.2297 ( 78%) [ Info: [ 16%] LOSS: training ≈ 0.2942 validation ≈ 0.2288 ( 78%) [ Info: [ 16%] LOSS: training ≈ 0.2935 validation ≈ 0.228 ( 78%) [ Info: [ 17%] LOSS: training ≈ 0.2927 validation ≈ 0.2272 ( 78%) [ Info: [ 18%] LOSS: training ≈ 0.292 validation ≈ 0.2265 ( 78%) [ Info: [ 18%] LOSS: training ≈ 0.2913 validation ≈ 0.2258 ( 78%) [ Info: [ 18%] LOSS: training ≈ 0.2907 validation ≈ 0.2251 ( 77%) [ Info: [ 19%] LOSS: training ≈ 0.2901 validation ≈ 0.2245 ( 77%) [ Info: [ 20%] LOSS: training ≈ 0.2894 validation ≈ 0.2239 ( 77%) [ Info: [ 20%] LOSS: training ≈ 0.2889 validation ≈ 0.2233 ( 77%) [ Info: [ 20%] LOSS: training ≈ 0.2883 validation ≈ 0.2227 ( 77%) [ Info: [ 21%] LOSS: training ≈ 0.2878 validation ≈ 0.2221 ( 77%) [ Info: [ 22%] LOSS: training ≈ 0.2872 validation ≈ 0.2216 ( 77%) [ Info: [ 22%] LOSS: training ≈ 0.2867 validation ≈ 0.2211 ( 77%) [ Info: [ 22%] LOSS: training ≈ 0.2862 validation ≈ 0.2206 ( 77%) [ Info: [ 23%] LOSS: training ≈ 0.2858 validation ≈ 0.2201 ( 77%) [ Info: [ 24%] LOSS: training ≈ 0.2853 validation ≈ 0.2196 ( 77%) [ Info: [ 24%] LOSS: training ≈ 0.2849 validation ≈ 0.2192 ( 77%) [ Info: [ 24%] LOSS: training ≈ 0.2844 validation ≈ 0.2188 ( 77%) [ Info: [ 25%] LOSS: training ≈ 0.284 validation ≈ 0.2183 ( 77%) [ Info: [ 26%] LOSS: training ≈ 0.2836 validation ≈ 0.2179 ( 77%) [ Info: [ 26%] LOSS: training ≈ 0.2832 validation ≈ 0.2175 ( 77%) [ Info: [ 26%] LOSS: training ≈ 0.2829 validation ≈ 0.2171 ( 77%) [ Info: [ 27%] LOSS: training ≈ 0.2825 validation ≈ 0.2168 ( 77%) [ Info: [ 28%] LOSS: training ≈ 0.2821 validation ≈ 0.2164 ( 77%) [ Info: [ 28%] LOSS: training ≈ 0.2818 validation ≈ 0.2161 ( 77%) [ Info: [ 28%] LOSS: training ≈ 0.2815 validation ≈ 0.2157 ( 77%) [ Info: [ 29%] LOSS: training ≈ 0.2811 validation ≈ 0.2154 ( 77%) [ Info: [ 30%] LOSS: training ≈ 0.2808 validation ≈ 0.2151 ( 77%) [ Info: [ 30%] LOSS: training ≈ 0.2805 validation ≈ 0.2148 ( 77%) [ Info: [ 30%] LOSS: training ≈ 0.2802 validation ≈ 0.2144 ( 77%) [ Info: [ 31%] LOSS: training ≈ 0.2799 validation ≈ 0.2141 ( 77%) [ Info: [ 32%] LOSS: training ≈ 0.2796 validation ≈ 0.2139 ( 76%) [ Info: [ 32%] LOSS: training ≈ 0.2794 validation ≈ 0.2136 ( 76%) [ Info: [ 32%] LOSS: training ≈ 0.2791 validation ≈ 0.2133 ( 76%) [ Info: [ 33%] LOSS: training ≈ 0.2788 validation ≈ 0.213 ( 76%) [ Info: [ 34%] LOSS: training ≈ 0.2786 validation ≈ 0.2128 ( 76%) [ Info: [ 34%] LOSS: training ≈ 0.2784 validation ≈ 0.2125 ( 76%) [ Info: [ 34%] LOSS: training ≈ 0.2781 validation ≈ 0.2123 ( 76%) [ Info: [ 35%] LOSS: training ≈ 0.2779 validation ≈ 0.212 ( 76%) [ Info: [ 36%] LOSS: training ≈ 0.2777 validation ≈ 0.2118 ( 76%) [ Info: [ 36%] LOSS: training ≈ 0.2774 validation ≈ 0.2115 ( 76%) [ Info: [ 36%] LOSS: training ≈ 0.2772 validation ≈ 0.2113 ( 76%) [ Info: [ 37%] LOSS: training ≈ 0.277 validation ≈ 0.2111 ( 76%) [ Info: [ 38%] LOSS: training ≈ 0.2768 validation ≈ 0.2109 ( 76%) [ Info: [ 38%] LOSS: training ≈ 0.2766 validation ≈ 0.2106 ( 76%) [ Info: [ 38%] LOSS: training ≈ 0.2764 validation ≈ 0.2104 ( 76%) [ Info: [ 39%] LOSS: training ≈ 0.2763 validation ≈ 0.2102 ( 76%) [ Info: [ 40%] LOSS: training ≈ 0.2761 validation ≈ 0.21 ( 76%) [ Info: [ 40%] LOSS: training ≈ 0.2759 validation ≈ 0.2098 ( 76%) [ Info: [ 40%] LOSS: training ≈ 0.2757 validation ≈ 0.2096 ( 76%) [ Info: [ 41%] LOSS: training ≈ 0.2756 validation ≈ 0.2094 ( 76%) [ Info: [ 42%] LOSS: training ≈ 0.2754 validation ≈ 0.2093 ( 76%) [ Info: [ 42%] LOSS: training ≈ 0.2752 validation ≈ 0.2091 ( 76%) [ Info: [ 42%] LOSS: training ≈ 0.2751 validation ≈ 0.2089 ( 76%) [ Info: [ 43%] LOSS: training ≈ 0.2749 validation ≈ 0.2087 ( 76%) [ Info: [ 44%] LOSS: training ≈ 0.2748 validation ≈ 0.2086 ( 76%) [ Info: [ 44%] LOSS: training ≈ 0.2746 validation ≈ 0.2084 ( 76%) [ Info: [ 44%] LOSS: training ≈ 0.2745 validation ≈ 0.2082 ( 76%) [ Info: [ 45%] LOSS: training ≈ 0.2744 validation ≈ 0.2081 ( 76%) [ Info: [ 46%] LOSS: training ≈ 0.2742 validation ≈ 0.2079 ( 76%) [ Info: [ 46%] LOSS: training ≈ 0.2741 validation ≈ 0.2078 ( 76%) [ Info: [ 46%] LOSS: training ≈ 0.274 validation ≈ 0.2076 ( 76%) [ Info: [ 47%] LOSS: training ≈ 0.2738 validation ≈ 0.2075 ( 76%) [ Info: [ 48%] LOSS: training ≈ 0.2737 validation ≈ 0.2073 ( 76%) [ Info: [ 48%] LOSS: training ≈ 0.2736 validation ≈ 0.2072 ( 76%) [ Info: [ 48%] LOSS: training ≈ 0.2735 validation ≈ 0.207 ( 76%) [ Info: [ 49%] LOSS: training ≈ 0.2734 validation ≈ 0.2069 ( 76%) [ Info: [ 50%] LOSS: training ≈ 0.2732 validation ≈ 0.2067 ( 76%) [ Info: [ 50%] LOSS: training ≈ 0.2731 validation ≈ 0.2066 ( 76%) [ Info: [ 50%] LOSS: training ≈ 0.273 validation ≈ 0.2065 ( 76%) [ Info: [ 51%] LOSS: training ≈ 0.2729 validation ≈ 0.2064 ( 76%) [ Info: [ 52%] LOSS: training ≈ 0.2728 validation ≈ 0.2062 ( 76%) [ Info: [ 52%] LOSS: training ≈ 0.2727 validation ≈ 0.2061 ( 76%) [ Info: [ 52%] LOSS: training ≈ 0.2726 validation ≈ 0.206 ( 76%) [ Info: [ 53%] LOSS: training ≈ 0.2725 validation ≈ 0.2059 ( 76%) [ Info: [ 54%] LOSS: training ≈ 0.2724 validation ≈ 0.2057 ( 76%) [ Info: [ 54%] LOSS: training ≈ 0.2723 validation ≈ 0.2056 ( 76%) [ Info: [ 55%] LOSS: training ≈ 0.2723 validation ≈ 0.2055 ( 75%) [ Info: [ 55%] LOSS: training ≈ 0.2722 validation ≈ 0.2054 ( 75%) [ Info: [ 56%] LOSS: training ≈ 0.2721 validation ≈ 0.2053 ( 75%) [ Info: [ 56%] LOSS: training ≈ 0.272 validation ≈ 0.2052 ( 75%) [ Info: [ 56%] LOSS: training ≈ 0.2719 validation ≈ 0.2051 ( 75%) [ Info: [ 57%] LOSS: training ≈ 0.2718 validation ≈ 0.205 ( 75%) [ Info: [ 57%] LOSS: training ≈ 0.2718 validation ≈ 0.2049 ( 75%) [ Info: [ 58%] LOSS: training ≈ 0.2717 validation ≈ 0.2048 ( 75%) [ Info: [ 58%] LOSS: training ≈ 0.2716 validation ≈ 0.2047 ( 75%) [ Info: [ 59%] LOSS: training ≈ 0.2715 validation ≈ 0.2046 ( 75%) [ Info: [ 60%] LOSS: training ≈ 0.2715 validation ≈ 0.2045 ( 75%) [ Info: [ 60%] LOSS: training ≈ 0.2714 validation ≈ 0.2044 ( 75%) [ Info: [ 60%] LOSS: training ≈ 0.2713 validation ≈ 0.2043 ( 75%) [ Info: [ 61%] LOSS: training ≈ 0.2712 validation ≈ 0.2042 ( 75%) [ Info: [ 62%] LOSS: training ≈ 0.2712 validation ≈ 0.2041 ( 75%) [ Info: [ 62%] LOSS: training ≈ 0.2711 validation ≈ 0.204 ( 75%) [ Info: [ 62%] LOSS: training ≈ 0.2711 validation ≈ 0.2039 ( 75%) [ Info: [ 63%] LOSS: training ≈ 0.271 validation ≈ 0.2039 ( 75%) [ Info: [ 64%] LOSS: training ≈ 0.2709 validation ≈ 0.2038 ( 75%) [ Info: [ 64%] LOSS: training ≈ 0.2709 validation ≈ 0.2037 ( 75%) [ Info: [ 64%] LOSS: training ≈ 0.2708 validation ≈ 0.2036 ( 75%) [ Info: [ 65%] LOSS: training ≈ 0.2707 validation ≈ 0.2035 ( 75%) [ Info: [ 66%] LOSS: training ≈ 0.2707 validation ≈ 0.2035 ( 75%) [ Info: [ 66%] LOSS: training ≈ 0.2706 validation ≈ 0.2034 ( 75%) [ Info: [ 66%] LOSS: training ≈ 0.2706 validation ≈ 0.2033 ( 75%) [ Info: [ 67%] LOSS: training ≈ 0.2705 validation ≈ 0.2032 ( 75%) [ Info: [ 68%] LOSS: training ≈ 0.2705 validation ≈ 0.2032 ( 75%) [ Info: [ 68%] LOSS: training ≈ 0.2704 validation ≈ 0.2031 ( 75%) [ Info: [ 68%] LOSS: training ≈ 0.2704 validation ≈ 0.203 ( 75%) [ Info: [ 69%] LOSS: training ≈ 0.2703 validation ≈ 0.2029 ( 75%) [ Info: [ 70%] LOSS: training ≈ 0.2703 validation ≈ 0.2029 ( 75%) [ Info: [ 70%] LOSS: training ≈ 0.2702 validation ≈ 0.2028 ( 75%) [ Info: [ 70%] LOSS: training ≈ 0.2702 validation ≈ 0.2027 ( 75%) [ Info: [ 71%] LOSS: training ≈ 0.2701 validation ≈ 0.2027 ( 75%) [ Info: [ 72%] LOSS: training ≈ 0.2701 validation ≈ 0.2026 ( 75%) [ Info: [ 72%] LOSS: training ≈ 0.27 validation ≈ 0.2025 ( 75%) [ Info: [ 72%] LOSS: training ≈ 0.27 validation ≈ 0.2025 ( 75%) [ Info: [ 73%] LOSS: training ≈ 0.2699 validation ≈ 0.2024 ( 75%) [ Info: [ 74%] LOSS: training ≈ 0.2699 validation ≈ 0.2024 ( 75%) [ Info: [ 74%] LOSS: training ≈ 0.2699 validation ≈ 0.2023 ( 75%) [ Info: [ 74%] LOSS: training ≈ 0.2698 validation ≈ 0.2022 ( 75%) [ Info: [ 75%] LOSS: training ≈ 0.2698 validation ≈ 0.2022 ( 75%) [ Info: [ 76%] LOSS: training ≈ 0.2697 validation ≈ 0.2021 ( 75%) [ Info: [ 76%] LOSS: training ≈ 0.2697 validation ≈ 0.2021 ( 75%) [ Info: [ 76%] LOSS: training ≈ 0.2696 validation ≈ 0.202 ( 75%) [ Info: [ 77%] LOSS: training ≈ 0.2696 validation ≈ 0.202 ( 75%) [ Info: [ 78%] LOSS: training ≈ 0.2696 validation ≈ 0.2019 ( 75%) [ Info: [ 78%] LOSS: training ≈ 0.2695 validation ≈ 0.2019 ( 75%) [ Info: [ 78%] LOSS: training ≈ 0.2695 validation ≈ 0.2018 ( 75%) [ Info: [ 79%] LOSS: training ≈ 0.2695 validation ≈ 0.2017 ( 75%) [ Info: [ 80%] LOSS: training ≈ 0.2694 validation ≈ 0.2017 ( 75%) [ Info: [ 80%] LOSS: training ≈ 0.2694 validation ≈ 0.2016 ( 75%) [ Info: [ 80%] LOSS: training ≈ 0.2694 validation ≈ 0.2016 ( 75%) [ Info: [ 81%] LOSS: training ≈ 0.2693 validation ≈ 0.2016 ( 75%) [ Info: [ 82%] LOSS: training ≈ 0.2693 validation ≈ 0.2015 ( 75%) [ Info: [ 82%] LOSS: training ≈ 0.2693 validation ≈ 0.2015 ( 75%) [ Info: [ 82%] LOSS: training ≈ 0.2692 validation ≈ 0.2014 ( 75%) [ Info: [ 83%] LOSS: training ≈ 0.2692 validation ≈ 0.2014 ( 75%) [ Info: [ 84%] LOSS: training ≈ 0.2692 validation ≈ 0.2013 ( 75%) [ Info: [ 84%] LOSS: training ≈ 0.2691 validation ≈ 0.2013 ( 75%) [ Info: [ 84%] LOSS: training ≈ 0.2691 validation ≈ 0.2012 ( 75%) [ Info: [ 85%] LOSS: training ≈ 0.2691 validation ≈ 0.2012 ( 75%) [ Info: [ 86%] LOSS: training ≈ 0.269 validation ≈ 0.2011 ( 75%) [ Info: [ 86%] LOSS: training ≈ 0.269 validation ≈ 0.2011 ( 75%) [ Info: [ 86%] LOSS: training ≈ 0.269 validation ≈ 0.2011 ( 75%) [ Info: [ 87%] LOSS: training ≈ 0.269 validation ≈ 0.201 ( 75%) [ Info: [ 88%] LOSS: training ≈ 0.2689 validation ≈ 0.201 ( 75%) [ Info: [ 88%] LOSS: training ≈ 0.2689 validation ≈ 0.2009 ( 75%) [ Info: [ 88%] LOSS: training ≈ 0.2689 validation ≈ 0.2009 ( 75%) [ Info: [ 89%] LOSS: training ≈ 0.2689 validation ≈ 0.2009 ( 75%) [ Info: [ 90%] LOSS: training ≈ 0.2688 validation ≈ 0.2008 ( 75%) [ Info: [ 90%] LOSS: training ≈ 0.2688 validation ≈ 0.2008 ( 75%) [ Info: [ 90%] LOSS: training ≈ 0.2688 validation ≈ 0.2008 ( 75%) [ Info: [ 91%] LOSS: training ≈ 0.2687 validation ≈ 0.2007 ( 75%) [ Info: [ 92%] LOSS: training ≈ 0.2687 validation ≈ 0.2007 ( 75%) [ Info: [ 92%] LOSS: training ≈ 0.2687 validation ≈ 0.2007 ( 75%) [ Info: [ 92%] LOSS: training ≈ 0.2687 validation ≈ 0.2006 ( 75%) [ Info: [ 93%] LOSS: training ≈ 0.2687 validation ≈ 0.2006 ( 75%) [ Info: [ 94%] LOSS: training ≈ 0.2686 validation ≈ 0.2006 ( 75%) [ Info: [ 94%] LOSS: training ≈ 0.2686 validation ≈ 0.2005 ( 75%) [ Info: [ 94%] LOSS: training ≈ 0.2686 validation ≈ 0.2005 ( 75%) [ Info: [ 95%] LOSS: training ≈ 0.2686 validation ≈ 0.2005 ( 75%) [ Info: [ 96%] LOSS: training ≈ 0.2685 validation ≈ 0.2004 ( 75%) [ Info: [ 96%] LOSS: training ≈ 0.2685 validation ≈ 0.2004 ( 75%) [ Info: [ 96%] LOSS: training ≈ 0.2685 validation ≈ 0.2004 ( 75%) [ Info: [ 97%] LOSS: training ≈ 0.2685 validation ≈ 0.2003 ( 75%) [ Info: [ 98%] LOSS: training ≈ 0.2685 validation ≈ 0.2003 ( 75%) [ Info: [ 98%] LOSS: training ≈ 0.2684 validation ≈ 0.2003 ( 75%) [ Info: [ 98%] LOSS: training ≈ 0.2684 validation ≈ 0.2003 ( 75%) [ Info: [ 99%] LOSS: training ≈ 0.2684 validation ≈ 0.2002 ( 75%) [ Info: [100%] LOSS: training ≈ 0.2684 validation ≈ 0.2002 ( 75%) [ Info: [100%] LOSS: training ≈ 0.2684 validation ≈ 0.2002 ( 75%) [ 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/9aijV/src/variables/selection.jl:90 ┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:90 [ Info: [ 2 vars.] MCC val. ≈ -0.0 [ Info: [ 3 vars.] MCC val. ≈ 0.545 [ Info: Optimal var. pool: [1, 12, 16] ┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:44 ┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:44 ┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:90 [ Info: [ 0 vars.] MCC val. ≈ -0.0 [ Info: [ 1 vars.] MCC val. ≈ 0.821 [ Info: [ 2 vars.] MCC val. ≈ 0.828 [ Info: [ 3 vars.] MCC val. ≈ 0.828 [ Info: [ 4 vars.] MCC val. ≈ 0.828 [ Info: [ 5 vars.] MCC val. ≈ 0.842 [ Info: Optimal var. pool: [8, 7, 2, 1, 3] ┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:44 [ Info: [19 vars.] MCC val. ≈ -0.0 [ Info: [18 vars.] MCC val. ≈ 0.504 [ Info: [17 vars.] MCC val. ≈ 0.788 [ Info: [16 vars.] MCC val. ≈ 0.804 [ Info: [15 vars.] MCC val. ≈ 0.81 [ Info: [14 vars.] MCC val. ≈ 0.817 [ Info: Optimal var. pool: [1, 2, 3, 5, 6, 7, 9, 10, 11, 13, 14, 15, 16, 18] ┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:44 [ Info: [ 9 vars.] MCC val. ≈ -0.0 [ Info: [ 8 vars.] MCC val. ≈ 0.752 [ Info: [ 7 vars.] MCC val. ≈ 0.773 [ Info: Optimal var. pool: [1, 2, 3, 6, 7, 8, 9] ┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:90 [ Info: [ 2 vars.] MCC val. ≈ -0.0 [ Info: [ 3 vars.] MCC val. ≈ 0.439 [ Info: Optimal var. pool: [12, 13, 1] ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/vif.jl:24 ┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead └ @ SDeMo ~/.julia/packages/SDeMo/9aijV/src/variables/selection.jl:90 [ Info: [ 0 vars.] MCC val. ≈ -0.0 [ Info: [ 1 vars.] MCC val. ≈ 0.786 [ Info: [ 2 vars.] MCC val. ≈ 0.801 [ Info: Optimal var. pool: [5, 15] Test Summary: | Pass Total Time Package | 297 297 20m13.3s Testing SDeMo tests passed Testing completed after 1267.47s PkgEval succeeded after 1346.15s