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Fold performances of “SVM MBO No Filter” on the HR Task
Plot | RMSE |
Luiando | 9.00 |
Laukiz1 | 21.17 |
Laukiz2 | 54.26 |
Oiartzun | 28.05 |
Overall leaderboard across all settings, sorted descending by performance.
Task | Model | Filter | RMSE | SE |
HR-NRI | SVM | Car | 27.983 | 19.193 |
HR-NRI-VI | SVM | Relief | 28.049 | 19.124 |
HR-NRI | SVM | Relief | 28.117 | 19.125 |
HR | SVM | Car | 28.122 | 19.123 |
HR | SVM | Info Gain | 28.122 | 19.123 |
VI | SVM | Relief | 28.122 | 19.113 |
HR | SVM | CMIM | 28.122 | 19.123 |
NRI-VI | SVM | PCA | 28.122 | 19.123 |
HR-NRI-VI | SVM | PCA | 28.122 | 19.123 |
VI | SVM | No Filter | 28.122 | 19.123 |
HR-NRI | SVM | No Filter | 28.122 | 19.123 |
HR-NRI-VI | SVM | No Filter | 28.122 | 19.123 |
NRI-VI | SVM | Car | 28.123 | 19.123 |
HR | SVM | Relief | 28.123 | 19.122 |
HR | SVM | Pearson | 28.123 | 19.123 |
HR | SVM | Borda | 28.123 | 19.123 |
NRI | SVM | PCA | 28.123 | 19.123 |
HR-NRI | SVM | PCA | 28.123 | 19.123 |
HR | SVM | No Filter | 28.123 | 19.123 |
NRI | SVM | No Filter | 28.123 | 19.123 |
NRI-VI | SVM | No Filter | 28.123 | 19.123 |
HR | SVM | PCA | 28.125 | 19.122 |
VI | SVM | Info Gain | 28.126 | 19.123 |
VI | SVM | MRMR | 28.130 | 19.114 |
HR-NRI-VI | SVM | CMIM | 28.130 | 19.114 |
VI | SVM | Borda | 28.135 | 19.146 |
NRI-VI | SVM | Borda | 28.140 | 19.099 |
VI | SVM | PCA | 28.143 | 19.093 |
NRI-VI | SVM | MRMR | 28.144 | 19.142 |
HR | SVM | MRMR | 28.153 | 19.123 |
HR-NRI-VI | SVM | Info Gain | 28.162 | 19.077 |
HR-NRI-VI | SVM | MRMR | 28.163 | 19.051 |
VI | SVM | Pearson | 28.171 | 19.212 |
NRI | SVM | Pearson | 28.186 | 19.121 |
NRI | SVM | Relief | 28.188 | 19.022 |
VI | SVM | CMIM | 28.188 | 19.200 |
NRI | SVM | Borda | 28.198 | 19.024 |
NRI-VI | SVM | Pearson | 28.209 | 19.193 |
VI | SVM | Car | 28.212 | 19.109 |
HR-NRI-VI | SVM | Pearson | 28.227 | 19.169 |
HR-NRI | SVM | Info Gain | 28.238 | 18.987 |
HR-NRI-VI | SVM | Car | 28.280 | 18.919 |
NRI | SVM | CMIM | 28.300 | 18.889 |
HR-NRI | SVM | Borda | 28.307 | 18.912 |
NRI-VI | SVM | CMIM | 28.348 | 18.826 |
HR-NRI | SVM | MRMR | 28.511 | 18.610 |
NRI | SVM | MRMR | 28.517 | 18.607 |
NRI-VI | SVM | Relief | 28.622 | 18.824 |
HR-NRI | SVM | CMIM | 28.683 | 18.395 |
HR-NRI-VI | SVM | Borda | 28.914 | 18.109 |
NRI | SVM | Car | 28.947 | 18.602 |
NRI-VI | SVM | Info Gain | 29.158 | 17.712 |
HR-NRI | SVM | Pearson | 30.978 | 18.394 |
HR-NRI | RF | Car | 31.077 | 17.093 |
NRI-VI | XGBOOST | Relief | 32.103 | 17.730 |
HR-NRI-VI | XGBOOST | MRMR | 32.313 | 17.381 |
NRI | SVM | Info Gain | 32.354 | 18.629 |
HR-NRI-VI | RF | Car | 32.451 | 15.894 |
NRI | XGBOOST | No Filter | 32.556 | 16.516 |
HR-NRI | XGBOOST | Relief | 32.566 | 15.251 |
NRI-VI | RF | PCA | 32.708 | 16.423 |
NRI | Ridge-CV | No Filter | 32.974 | 7.237 |
HR-NRI-VI | XGBOOST | CMIM | 33.084 | 15.219 |
NRI | RF | PCA | 33.311 | 15.957 |
HR-NRI-VI | RF | PCA | 33.370 | 15.964 |
HR-NRI | RF | PCA | 33.598 | 15.604 |
HR-NRI-VI | XGBOOST | Car | 33.692 | 14.135 |
HR-NRI-VI | XGBOOST | Info Gain | 33.772 | 15.459 |
NRI | XGBOOST | Borda | 34.012 | 15.435 |
HR-NRI | RF | Borda | 34.077 | 14.375 |
NRI-VI | XGBOOST | CMIM | 34.423 | 13.880 |
HR | RF | Car | 34.467 | 12.604 |
HR-NRI | XGBOOST | Car | 34.537 | 15.019 |
NRI | XGBOOST | Car | 34.546 | 13.779 |
NRI | XGBOOST | Pearson | 34.612 | 14.619 |
NRI-VI | XGBOOST | Info Gain | 34.690 | 15.672 |
NRI-VI | RF | Car | 34.813 | 13.146 |
HR-NRI-VI | XGBOOST | Borda | 35.024 | 14.277 |
NRI-VI | XGBOOST | Borda | 35.085 | 15.110 |
HR | XGBOOST | Car | 35.094 | 13.624 |
NRI | RF | MRMR | 35.109 | 13.318 |
NRI | RF | Car | 35.182 | 12.041 |
NRI | RF | Borda | 35.182 | 12.301 |
HR-NRI-VI | RF | MRMR | 35.230 | 13.808 |
NRI-VI | XGBOOST | Car | 35.238 | 13.304 |
HR-NRI | XGBOOST | Pearson | 35.262 | 13.043 |
HR | RF | Info Gain | 35.271 | 12.755 |
HR-NRI | XGBOOST | CMIM | 35.315 | 13.794 |
NRI-VI | RF | CMIM | 35.330 | 14.913 |
HR-NRI | XGBOOST | Info Gain | 35.367 | 14.339 |
HR-NRI-VI | XGBOOST | Pearson | 35.370 | 14.406 |
NRI-VI | RF | MRMR | 35.511 | 14.834 |
HR-NRI-VI | RF | Borda | 35.527 | 13.643 |
NRI | XGBOOST | CMIM | 35.535 | 13.654 |
HR-NRI | RF | Pearson | 35.556 | 13.076 |
HR-NRI-VI | XGBOOST | Relief | 35.556 | 14.832 |
NRI | RF | CMIM | 35.629 | 13.644 |
NRI-VI | XGBOOST | Pearson | 35.660 | 13.066 |
HR-NRI | XGBOOST | Borda | 35.662 | 13.289 |
HR-NRI | RF | MRMR | 35.697 | 14.425 |
NRI | XGBOOST | Info Gain | 35.728 | 14.460 |
HR-NRI-VI | XGBOOST | No Filter | 35.762 | 12.884 |
HR-NRI-VI | RF | No Filter | 35.867 | 12.747 |
NRI | RF | Info Gain | 35.980 | 13.862 |
HR-NRI-VI | RF | CMIM | 36.087 | 14.219 |
NRI-VI | RF | Borda | 36.183 | 13.091 |
HR-NRI | XGBOOST | No Filter | 36.187 | 10.588 |
HR-NRI | RF | No Filter | 36.211 | 12.830 |
NRI-VI | RF | No Filter | 36.344 | 12.844 |
NRI | RF | No Filter | 36.389 | 12.483 |
NRI-VI | RF | Info Gain | 36.406 | 13.666 |
HR-NRI | RF | Info Gain | 36.671 | 13.625 |
NRI-VI | XGBOOST | MRMR | 36.700 | 13.207 |
HR-NRI | XGBOOST | MRMR | 36.700 | 11.892 |
NRI | XGBOOST | MRMR | 36.731 | 11.896 |
HR-NRI | RF | CMIM | 36.741 | 13.790 |
NRI-VI | RF | Pearson | 36.755 | 13.206 |
HR-NRI-VI | RF | Info Gain | 36.813 | 13.486 |
HR-NRI-VI | RF | Pearson | 36.837 | 13.846 |
NRI | RF | Pearson | 36.842 | 13.567 |
HR | RF | PCA | 37.096 | 12.302 |
NRI-VI | XGBOOST | No Filter | 37.143 | 12.421 |
HR | XGBOOST | Pearson | 37.239 | 14.416 |
HR | XGBOOST | Relief | 37.307 | 10.286 |
HR | RF | Borda | 37.342 | 13.099 |
HR | RF | Pearson | 37.351 | 13.852 |
NRI | XGBOOST | Relief | 37.539 | 10.630 |
HR | XGBOOST | MRMR | 37.774 | 12.026 |
VI | RF | MRMR | 38.320 | 11.654 |
HR-NRI-VI | RF | Relief | 38.450 | 8.774 |
HR-NRI | RF | Relief | 38.598 | 8.998 |
NRI-VI | RF | Relief | 38.621 | 8.764 |
VI | RF | No Filter | 38.698 | 10.946 |
VI | RF | Relief | 38.879 | 11.204 |
VI | RF | Borda | 38.974 | 11.901 |
NRI | RF | Relief | 38.985 | 8.031 |
HR | XGBOOST | Info Gain | 39.214 | 12.433 |
HR | RF | CMIM | 39.437 | 8.018 |
VI | RF | Car | 39.901 | 12.918 |
VI | XGBOOST | Relief | 39.903 | 9.438 |
VI | RF | Info Gain | 39.907 | 9.395 |
VI | RF | CMIM | 40.046 | 9.784 |
VI | RF | Pearson | 40.247 | 9.882 |
HR-NRI | Ridge-CV | No Filter | 40.271 | 10.513 |
VI | XGBOOST | Info Gain | 40.301 | 10.101 |
VI | XGBOOST | Pearson | 40.361 | 9.898 |
HR | Ridge-CV | No Filter | 40.520 | 11.207 |
HR-NRI-VI | XGBOOST | PCA | 40.535 | 11.371 |
VI | RF | PCA | 40.761 | 8.516 |
NRI | XGBOOST | PCA | 40.797 | 11.785 |
HR | XGBOOST | CMIM | 40.960 | 9.937 |
HR-NRI | XGBOOST | PCA | 40.974 | 10.499 |
HR | RF | No Filter | 41.067 | 8.444 |
HR | RF | Relief | 41.302 | 10.593 |
VI | XGBOOST | CMIM | 41.639 | 10.152 |
HR | XGBOOST | Borda | 42.073 | 14.376 |
VI | XGBOOST | PCA | 42.115 | 7.037 |
HR | RF | MRMR | 42.423 | 7.454 |
HR | XGBOOST | PCA | 43.129 | 7.629 |
NRI-VI | XGBOOST | PCA | 43.312 | 8.997 |
VI | XGBOOST | No Filter | 44.444 | 8.759 |
HR | Lasso-CV | No Filter | 45.960 | 18.350 |
NRI | Lasso-CV | No Filter | 46.331 | 20.036 |
VI | XGBOOST | Borda | 46.502 | 4.109 |
VI | XGBOOST | MRMR | 46.520 | 5.598 |
HR-NRI | Lasso-CV | No Filter | 46.653 | 20.279 |
VI | XGBOOST | Car | 46.682 | 7.759 |
HR | XGBOOST | No Filter | 49.382 | 1.358 |
NRI-VI | Lasso-CV | No Filter | 54.497 | 24.638 |
HR-NRI-VI | Lasso-CV | No Filter | 54.497 | 24.638 |
VI | Lasso-CV | No Filter | 55.325 | 23.009 |
HR-NRI-VI | Ridge-CV | No Filter | 9230336.565 | 18460539.886 |
NRI-VI | Ridge-CV | No Filter | 9409773.079 | 18819412.914 |
VI | Ridge-CV | No Filter | 11337132.755 | 22674132.319 |
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 |
HR-NRI | SVM | Car | 27.983 | 19.193 |
HR-NRI | RF | Car | 31.077 | 17.093 |
NRI-VI | XGBOOST | Relief | 32.103 | 17.730 |
NRI | Ridge-CV | No Filter | 32.974 | 7.237 |
HR | Lasso-CV | No Filter | 45.960 | 18.350 |
Version | Author | Date |
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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_7.10.0
loaded via a namespace (and not attached):
[1] fs_1.3.1 filelock_1.0.2 RColorBrewer_1.1-2
[4] httr_1.4.0 rprojroot_1.3-2 tools_3.6.1
[7] backports_1.1.5 R6_2.4.1 vipor_0.4.5
[10] lazyeval_0.2.1 colorspace_1.4-0 withr_2.1.2
[13] mco_1.0-15.1 compiler_3.6.1 git2r_0.26.1
[16] parallelMap_1.4 xml2_1.2.2 plotly_4.8.0
[19] officer_0.3.7 labeling_0.3 scales_1.0.0
[22] checkmate_1.9.1 plot3D_1.1.1 systemfonts_0.1.1
[25] stringr_1.4.0 digest_0.6.23 txtq_0.1.4
[28] rmarkdown_1.13 R.utils_2.8.0 smoof_1.5.1
[31] base64enc_0.1-3 pkgconfig_2.0.3 htmltools_0.3.6
[34] lhs_1.0.1 htmlwidgets_1.3 rlang_0.4.4
[37] BBmisc_1.11 mlrMBO_1.1.2 jsonlite_1.6
[40] zip_2.0.4 R.oo_1.23.0 Matrix_1.2-15
[43] Rcpp_1.0.3 munsell_0.5.0 gdtools_0.2.1
[46] lifecycle_0.1.0 R.methodsS3_1.7.1 stringi_1.3.1
[49] whisker_0.3-2 yaml_2.2.0 storr_1.2.1
[52] RJSONIO_1.3-1.1 grid_3.6.1 misc3d_0.8-4
[55] parallel_3.6.1 promises_1.0.1 crayon_1.3.4
[58] lattice_0.20-38 splines_3.6.1 zeallot_0.1.0
[61] knitr_1.23 pillar_1.4.3 igraph_1.2.4.1
[64] uuid_0.1-2 base64url_1.4 fastmatch_1.1-0
[67] glue_1.3.1 evaluate_0.13 data.table_1.12.6
[70] vctrs_0.2.1 httpuv_1.4.5.1 gtable_0.2.0
[73] purrr_0.3.3 tidyr_1.0.0 assertthat_0.2.1
[76] xfun_0.5 later_1.0.0 survival_2.43-3
[79] viridisLite_0.3.0 tibble_2.1.3 beeswarm_0.2.3
[82] workflowr_1.6.0 ellipsis_0.3.0