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Last update:
[1] "Sat Apr 18 16:25:36 2020"Fold performances of “SVM MBO No Filter” on the HR Task
Plot | RMSE |
Luiando | 21.17 |
Laukiz1 | 28.05 |
Laukiz2 | 9.00 |
Oiartzun | 54.26 |
Overall leaderboard across all settings, sorted ascending by performance.
Task | Model | Filter | RMSE | SE |
NRI | SVM | Info Gain | 2.799100e+01 | 1.915200e+01 |
HR-NRI-VI | SVM | Relief | 2.806700e+01 | 1.914300e+01 |
VI | SVM | Relief | 2.809700e+01 | 1.913500e+01 |
HR-NRI-VI | SVM | Car | 2.810700e+01 | 1.912600e+01 |
HR-NRI | SVM | MRMR | 2.811700e+01 | 1.911300e+01 |
VI | SVM | Pearson | 2.811900e+01 | 1.909900e+01 |
HR-NRI | SVM | CMIM | 2.811900e+01 | 1.909000e+01 |
HR | SVM | Info Gain | 2.812200e+01 | 1.912300e+01 |
HR | SVM | CMIM | 2.812200e+01 | 1.912300e+01 |
NRI-VI | SVM | PCA | 2.812200e+01 | 1.912300e+01 |
HR-NRI | SVM | PCA | 2.812200e+01 | 1.912300e+01 |
HR-NRI-VI | SVM | PCA | 2.812200e+01 | 1.912300e+01 |
NRI-VI | SVM | No Filter | 2.812200e+01 | 1.912300e+01 |
HR-NRI | SVM | No Filter | 2.812200e+01 | 1.912300e+01 |
HR | SVM | Car | 2.812300e+01 | 1.912300e+01 |
HR | SVM | Borda | 2.812300e+01 | 1.912300e+01 |
NRI | SVM | PCA | 2.812300e+01 | 1.912300e+01 |
HR | SVM | No Filter | 2.812300e+01 | 1.912300e+01 |
VI | SVM | No Filter | 2.812300e+01 | 1.912300e+01 |
NRI | SVM | No Filter | 2.812300e+01 | 1.912300e+01 |
HR-NRI-VI | SVM | No Filter | 2.812300e+01 | 1.912300e+01 |
HR | SVM | Pearson | 2.812400e+01 | 1.912300e+01 |
NRI-VI | SVM | Car | 2.812500e+01 | 1.912900e+01 |
VI | SVM | MRMR | 2.812500e+01 | 1.911900e+01 |
HR | SVM | PCA | 2.812500e+01 | 1.912200e+01 |
VI | SVM | Info Gain | 2.812600e+01 | 1.912300e+01 |
HR-NRI-VI | SVM | MRMR | 2.812600e+01 | 1.910000e+01 |
HR | SVM | Relief | 2.813000e+01 | 1.911400e+01 |
HR-NRI-VI | SVM | Borda | 2.813300e+01 | 1.936200e+01 |
VI | SVM | PCA | 2.814400e+01 | 1.909100e+01 |
HR | SVM | MRMR | 2.815300e+01 | 1.912300e+01 |
VI | SVM | Borda | 2.815500e+01 | 1.918300e+01 |
NRI-VI | SVM | CMIM | 2.815700e+01 | 1.907700e+01 |
HR-NRI-VI | SVM | CMIM | 2.816200e+01 | 1.907100e+01 |
VI | SVM | CMIM | 2.816900e+01 | 1.921800e+01 |
HR-NRI | SVM | Info Gain | 2.817500e+01 | 1.913100e+01 |
NRI-VI | SVM | Borda | 2.818100e+01 | 1.904500e+01 |
HR-NRI-VI | SVM | Info Gain | 2.820400e+01 | 1.902300e+01 |
HR-NRI | SVM | Borda | 2.820500e+01 | 1.900700e+01 |
HR-NRI | SVM | Pearson | 2.821300e+01 | 1.915100e+01 |
VI | SVM | Car | 2.826300e+01 | 1.927700e+01 |
NRI | SVM | Pearson | 2.832100e+01 | 1.894200e+01 |
HR-NRI | SVM | Relief | 2.833700e+01 | 1.884000e+01 |
HR-NRI | SVM | Car | 2.838400e+01 | 1.876200e+01 |
NRI | SVM | Car | 2.840300e+01 | 1.874400e+01 |
NRI-VI | SVM | MRMR | 2.844000e+01 | 1.875300e+01 |
HR-NRI-VI | SVM | Pearson | 2.846900e+01 | 1.864000e+01 |
NRI | SVM | MRMR | 2.851700e+01 | 1.860700e+01 |
NRI-VI | SVM | Relief | 2.857500e+01 | 1.871000e+01 |
NRI | SVM | CMIM | 2.865700e+01 | 1.842800e+01 |
NRI-VI | SVM | Info Gain | 2.866400e+01 | 1.829900e+01 |
NRI | SVM | Borda | 2.867900e+01 | 1.840000e+01 |
NRI-VI | SVM | Pearson | 2.873800e+01 | 1.853400e+01 |
NRI | RF | Car | 3.077400e+01 | 1.686100e+01 |
VI | Lasso-MBO | No Filter | 3.100900e+01 | 1.471400e+01 |
HR-NRI-VI | XGBOOST | Borda | 3.105200e+01 | 1.700900e+01 |
HR-NRI | XGBOOST | CMIM | 3.108900e+01 | 1.657600e+01 |
NRI | Lasso-MBO | No Filter | 3.116500e+01 | 1.502500e+01 |
NRI | Ridge-MBO | No Filter | 3.116500e+01 | 1.502500e+01 |
NRI-VI | Lasso-MBO | No Filter | 3.120100e+01 | 1.508900e+01 |
HR-NRI | Lasso-MBO | No Filter | 3.120100e+01 | 1.508900e+01 |
HR-NRI-VI | Lasso-MBO | No Filter | 3.120100e+01 | 1.508900e+01 |
NRI-VI | XGBOOST | Car | 3.208200e+01 | 1.767200e+01 |
NRI-VI | XGBOOST | MRMR | 3.259500e+01 | 1.627900e+01 |
NRI-VI | XGBOOST | CMIM | 3.272100e+01 | 1.543600e+01 |
HR-NRI | XGBOOST | Relief | 3.274300e+01 | 1.409400e+01 |
NRI | RF | PCA | 3.296600e+01 | 1.616100e+01 |
NRI | RF | Borda | 3.305000e+01 | 1.485800e+01 |
NRI-VI | RF | PCA | 3.309600e+01 | 1.600100e+01 |
NRI | XGBOOST | Car | 3.315400e+01 | 1.640300e+01 |
HR-NRI | RF | PCA | 3.325500e+01 | 1.572300e+01 |
NRI-VI | XGBOOST | No Filter | 3.350500e+01 | 1.459900e+01 |
HR-NRI-VI | RF | PCA | 3.358800e+01 | 1.571000e+01 |
HR-NRI-VI | RF | Car | 3.377900e+01 | 1.429700e+01 |
HR-NRI | RF | Car | 3.404400e+01 | 1.343400e+01 |
NRI | XGBOOST | CMIM | 3.416800e+01 | 1.557100e+01 |
HR-NRI-VI | XGBOOST | MRMR | 3.417000e+01 | 1.494000e+01 |
NRI | SVM | Relief | 3.417700e+01 | 1.990500e+01 |
NRI | XGBOOST | Pearson | 3.420900e+01 | 1.224600e+01 |
HR-NRI | XGBOOST | Pearson | 3.423400e+01 | 1.373400e+01 |
NRI | XGBOOST | MRMR | 3.439300e+01 | 1.403700e+01 |
HR | RF | Car | 3.446700e+01 | 1.260400e+01 |
HR-NRI-VI | XGBOOST | Pearson | 3.451600e+01 | 1.425300e+01 |
NRI-VI | XGBOOST | Info Gain | 3.451800e+01 | 1.500500e+01 |
HR-NRI | XGBOOST | Borda | 3.459000e+01 | 1.488700e+01 |
NRI-VI | XGBOOST | Relief | 3.470900e+01 | 1.451300e+01 |
NRI | RF | CMIM | 3.473400e+01 | 1.373300e+01 |
HR | XGBOOST | Borda | 3.474800e+01 | 1.357200e+01 |
HR-NRI-VI | RF | CMIM | 3.476500e+01 | 1.382300e+01 |
NRI-VI | XGBOOST | Pearson | 3.477100e+01 | 1.353400e+01 |
HR-NRI-VI | XGBOOST | No Filter | 3.477400e+01 | 1.380400e+01 |
HR | XGBOOST | Relief | 3.477500e+01 | 1.331700e+01 |
HR-NRI-VI | XGBOOST | CMIM | 3.479700e+01 | 1.475800e+01 |
HR-NRI-VI | XGBOOST | Car | 3.480000e+01 | 1.470200e+01 |
HR | XGBOOST | Car | 3.480600e+01 | 1.291500e+01 |
NRI | RF | MRMR | 3.484300e+01 | 1.393700e+01 |
HR-NRI | RF | MRMR | 3.489500e+01 | 1.378100e+01 |
HR-NRI-VI | XGBOOST | Info Gain | 3.490000e+01 | 1.361800e+01 |
NRI | XGBOOST | Info Gain | 3.490400e+01 | 1.579900e+01 |
HR-NRI | XGBOOST | No Filter | 3.496300e+01 | 1.376900e+01 |
NRI-VI | RF | Car | 3.499600e+01 | 1.330800e+01 |
HR-NRI-VI | RF | MRMR | 3.500700e+01 | 1.363400e+01 |
NRI-VI | RF | CMIM | 3.518900e+01 | 1.417200e+01 |
NRI-VI | RF | MRMR | 3.522300e+01 | 1.412900e+01 |
HR-NRI-VI | XGBOOST | Relief | 3.524600e+01 | 1.282000e+01 |
HR | Lasso-MBO | No Filter | 3.526100e+01 | 1.224300e+01 |
HR | XGBOOST | CMIM | 3.527600e+01 | 1.366500e+01 |
HR | XGBOOST | Pearson | 3.532500e+01 | 1.367800e+01 |
HR | Ridge-MBO | No Filter | 3.545300e+01 | 1.265500e+01 |
HR | RF | Borda | 3.559300e+01 | 1.294900e+01 |
NRI-VI | XGBOOST | Borda | 3.560800e+01 | 1.182300e+01 |
NRI | XGBOOST | Borda | 3.564000e+01 | 1.236400e+01 |
NRI-VI | RF | Borda | 3.569100e+01 | 1.405100e+01 |
HR | RF | Info Gain | 3.582500e+01 | 1.384800e+01 |
HR-NRI | XGBOOST | Info Gain | 3.584200e+01 | 1.454300e+01 |
NRI | RF | No Filter | 3.586800e+01 | 1.287300e+01 |
HR | XGBOOST | MRMR | 3.586900e+01 | 1.386600e+01 |
NRI-VI | RF | No Filter | 3.599900e+01 | 1.289500e+01 |
NRI | XGBOOST | No Filter | 3.605100e+01 | 1.160400e+01 |
NRI | XGBOOST | Relief | 3.606200e+01 | 1.277900e+01 |
HR-NRI | RF | Borda | 3.607400e+01 | 1.378700e+01 |
HR-NRI | RF | No Filter | 3.622200e+01 | 1.283300e+01 |
HR-NRI | RF | CMIM | 3.631700e+01 | 1.414400e+01 |
HR-NRI-VI | RF | No Filter | 3.635600e+01 | 1.263800e+01 |
HR-NRI | RF | Info Gain | 3.643200e+01 | 1.394300e+01 |
NRI | RF | Info Gain | 3.645200e+01 | 1.382700e+01 |
HR-NRI-VI | RF | Info Gain | 3.656000e+01 | 1.371300e+01 |
NRI-VI | RF | Info Gain | 3.657500e+01 | 1.385600e+01 |
HR-NRI-VI | RF | Borda | 3.665400e+01 | 1.305000e+01 |
HR-NRI | RF | Pearson | 3.688300e+01 | 1.361900e+01 |
NRI-VI | RF | Pearson | 3.690300e+01 | 1.349500e+01 |
HR | RF | Pearson | 3.692000e+01 | 1.445700e+01 |
HR-NRI | XGBOOST | MRMR | 3.701000e+01 | 1.314700e+01 |
NRI | RF | Pearson | 3.714100e+01 | 1.326600e+01 |
VI | XGBOOST | Relief | 3.714700e+01 | 1.426200e+01 |
HR | RF | PCA | 3.715300e+01 | 1.232900e+01 |
HR-NRI-VI | RF | Pearson | 3.730000e+01 | 1.344300e+01 |
NRI | RF | Relief | 3.737600e+01 | 9.425000e+00 |
HR-NRI | XGBOOST | Car | 3.757200e+01 | 1.110100e+01 |
HR-NRI | RF | Relief | 3.769000e+01 | 9.839000e+00 |
VI | RF | MRMR | 3.818100e+01 | 1.225500e+01 |
NRI | XGBOOST | PCA | 3.842900e+01 | 1.498200e+01 |
NRI-VI | RF | Relief | 3.849800e+01 | 8.671000e+00 |
HR-NRI-VI | RF | Relief | 3.849800e+01 | 8.909000e+00 |
VI | RF | No Filter | 3.875400e+01 | 1.127100e+01 |
VI | RF | Borda | 3.884000e+01 | 1.123700e+01 |
HR | RF | CMIM | 3.968700e+01 | 8.106000e+00 |
VI | XGBOOST | Info Gain | 3.987200e+01 | 1.088000e+01 |
VI | RF | Info Gain | 3.992000e+01 | 9.458000e+00 |
HR | XGBOOST | Info Gain | 4.007000e+01 | 1.074300e+01 |
VI | RF | CMIM | 4.009900e+01 | 9.758000e+00 |
VI | RF | Pearson | 4.017500e+01 | 9.959000e+00 |
HR-NRI-VI | XGBOOST | PCA | 4.018500e+01 | 1.139100e+01 |
VI | RF | Relief | 4.044900e+01 | 8.367000e+00 |
NRI-VI | XGBOOST | PCA | 4.056700e+01 | 1.083900e+01 |
VI | RF | Car | 4.058100e+01 | 1.244800e+01 |
VI | RF | PCA | 4.071900e+01 | 8.567000e+00 |
HR | RF | Relief | 4.165600e+01 | 1.064000e+01 |
VI | XGBOOST | CMIM | 4.172700e+01 | 9.810000e+00 |
HR | RF | No Filter | 4.188400e+01 | 7.806000e+00 |
HR | XGBOOST | PCA | 4.214800e+01 | 8.077000e+00 |
HR | RF | MRMR | 4.231200e+01 | 7.705000e+00 |
HR-NRI | XGBOOST | PCA | 4.257800e+01 | 8.278000e+00 |
VI | XGBOOST | PCA | 4.366700e+01 | 8.067000e+00 |
VI | XGBOOST | Pearson | 4.461000e+01 | 5.783000e+00 |
VI | XGBOOST | No Filter | 4.568900e+01 | 5.304000e+00 |
VI | XGBOOST | Borda | 4.604100e+01 | 3.871000e+00 |
VI | XGBOOST | MRMR | 4.625600e+01 | 9.422000e+00 |
VI | XGBOOST | Car | 4.639900e+01 | 7.575000e+00 |
HR | XGBOOST | No Filter | 4.680000e+01 | 3.921000e+00 |
NRI-VI | Ridge-MBO | No Filter | 1.165847e+10 | 2.331694e+10 |
HR-NRI-VI | Ridge-MBO | No Filter | 1.263193e+10 | 2.526387e+10 |
HR-NRI | Ridge-MBO | No Filter | 1.265012e+10 | 2.530024e+10 |
VI | Ridge-MBO | No Filter | 4.935939e+10 | 9.871879e+10 |
Learners: On which task and using which filter did every learner score their best result on?
*CV: L2 penalized regression using the internal 10-fold CV tuning of the glmnet package
*MBO: L2 penalized regression using using MBO for hyperparameter optimization.
Task | Model | Filter | RMSE | SE |
NRI | SVM | Info Gain | 27.991 | 19.152 |
NRI | RF | Car | 30.774 | 16.861 |
VI | Lasso-MBO | No Filter | 31.009 | 14.714 |
HR-NRI-VI | XGBOOST | Borda | 31.052 | 17.009 |
NRI | Ridge-MBO | No Filter | 31.165 | 15.025 |
Overall leaderboard across all settings, sorted descending by performance.
Task | Model | Filter | RMSE | SE |
VI | Ridge-MBO | No Filter | 4.935939e+10 | 9.871879e+10 |
HR-NRI | Ridge-MBO | No Filter | 1.265012e+10 | 2.530024e+10 |
HR-NRI-VI | Ridge-MBO | No Filter | 1.263193e+10 | 2.526387e+10 |
NRI-VI | Ridge-MBO | No Filter | 1.165847e+10 | 2.331694e+10 |
HR | XGBOOST | No Filter | 4.680000e+01 | 3.921000e+00 |
VI | XGBOOST | Car | 4.639900e+01 | 7.575000e+00 |
VI | XGBOOST | MRMR | 4.625600e+01 | 9.422000e+00 |
VI | XGBOOST | Borda | 4.604100e+01 | 3.871000e+00 |
VI | XGBOOST | No Filter | 4.568900e+01 | 5.304000e+00 |
VI | XGBOOST | Pearson | 4.461000e+01 | 5.783000e+00 |
| Version | Author | Date |
|---|---|---|
| 544e288 | pat-s | 2020-04-12 |
| f59d02a | pat-s | 2020-03-05 |
| 2ee982d | pat-s | 2020-03-05 |
| 274a918 | pat-s | 2020-02-25 |
| b25e779 | pat-s | 2020-01-10 |
| 7f9507f | pat-s | 2019-12-10 |
| 482a158 | pat-s | 2019-11-01 |
| becf5ea | pat-s | 2019-11-01 |
| bd7c7f5 | pat-s | 2019-10-31 |
| 62ff96f | pat-s | 2019-10-07 |
| a947654 | pat-s | 2019-10-02 |
| 49da171 | pat-s | 2019-09-22 |
| 41aae14 | pat-s | 2019-09-12 |
| b181c52 | pat-s | 2019-09-02 |
| 8e7e4fe | pat-s | 2019-09-01 |
| 7582c67 | pat-s | 2019-08-31 |
| abd531f | pat-s | 2019-08-31 |
Showing the final effect of applying feature selection to a learner for each task. All filters are colored in the same way whereas using “no filter” appears in a different color.
Showing the final effect of applying feature selection to a learner for each task. All filters are summarized into a a single color whereas the “Borda” filter appears in its own color.
R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)
Matrix products: default
BLAS: /opt/spack/opt/spack/linux-centos7-x86_64/gcc-9.2.0/r-3.6.1-j25wr6zcofibs2zfjwg37357rjj26lqb/rlib/R/lib/libRblas.so
LAPACK: /opt/spack/opt/spack/linux-centos7-x86_64/gcc-9.2.0/r-3.6.1-j25wr6zcofibs2zfjwg37357rjj26lqb/rlib/R/lib/libRlapack.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] forcats_0.4.0 dplyr_0.8.3 mlr_2.17.0.9001
[4] ParamHelpers_1.12 here_0.1 ggpubr_0.1.6
[7] magrittr_1.5 ggrepel_0.8.0 ggsci_2.9
[10] ggbeeswarm_0.7.0 ggplot2_3.2.1 flextable_0.5.8
[13] xtable_1.8-3 tidyselect_0.2.5 drake_7.12.0
loaded via a namespace (and not attached):
[1] fs_1.3.1 filelock_1.0.2 RColorBrewer_1.1-2
[4] progress_1.2.0 httr_1.4.0 rprojroot_1.3-2
[7] tools_3.6.1 backports_1.1.5 R6_2.4.1
[10] vipor_0.4.5 lazyeval_0.2.1 colorspace_1.4-0
[13] withr_2.1.2 prettyunits_1.0.2 mco_1.0-15.1
[16] compiler_3.6.1 git2r_0.26.1 parallelMap_1.4
[19] cli_2.0.1 xml2_1.2.2 plotly_4.8.0
[22] officer_0.3.7 labeling_0.3 scales_1.0.0
[25] checkmate_2.0.0 plot3D_1.1.1 systemfonts_0.1.1
[28] stringr_1.4.0 digest_0.6.23 txtq_0.1.4
[31] rmarkdown_1.13 R.utils_2.8.0 smoof_1.5.1
[34] base64enc_0.1-3 pkgconfig_2.0.3 htmltools_0.3.6
[37] lhs_1.0.1 htmlwidgets_1.3 rlang_0.4.4
[40] BBmisc_1.11 mlrMBO_1.1.2 jsonlite_1.6
[43] zip_2.0.4 R.oo_1.23.0 Matrix_1.2-15
[46] Rcpp_1.0.3 munsell_0.5.0 fansi_0.4.1
[49] gdtools_0.2.1 lifecycle_0.1.0 R.methodsS3_1.7.1
[52] stringi_1.3.1 whisker_0.3-2 yaml_2.2.0
[55] storr_1.2.1 RJSONIO_1.3-1.1 grid_3.6.1
[58] misc3d_0.8-4 parallel_3.6.1 promises_1.0.1
[61] crayon_1.3.4 lattice_0.20-38 splines_3.6.1
[64] hms_0.5.3 zeallot_0.1.0 knitr_1.23
[67] pillar_1.4.3 igraph_1.2.4.1 uuid_0.1-2
[70] base64url_1.4 fastmatch_1.1-0 glue_1.3.1
[73] evaluate_0.13 data.table_1.12.8 vctrs_0.2.1
[76] httpuv_1.4.5.1 gtable_0.3.0 purrr_0.3.3
[79] tidyr_1.0.0 assertthat_0.2.1 xfun_0.5
[82] later_1.0.0 survival_2.43-3 viridisLite_0.3.0
[85] tibble_2.1.3 beeswarm_0.2.3 workflowr_1.6.1
[88] ellipsis_0.3.0