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README.txt
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README.txt
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Interpretable Machine Learning for Survival Analysis
Sophie Hanna Langbein, Mateusz Krzyziński, Mikołaj Spytek, Hubert Baniecki, Przemysław Biecek, Marvin N. Wright
Author of the code: Sophie Hanna Langbein ([email protected], [email protected])
The R code can be found in utils.R, plotting_functions.R, simulation_example_ice_pdp.R and simulation_example_ale.R, simulation_example_fi.R, real_data_example.R
The code files need to be run in the following order: simulation_example_ice_pdp.R -> simulation_example_ale.R -> simulation_example_fi.R -> real_data_example.R
Files and Folder structure:
Folders:
data: folder containing the data to be analyzed
figures_iml: folder in which all figures generated in the code and contained in the paper are saved
files:
utils.R: code file containing helper functions
plotting_functions.R: code file containing plotting functions
simulation_example_ice_pdp.R: code file containing the simulation example for permutation feature importance, individual conditional expectation plots and partial dependence plots in the methods section of the paper
simulation_example_ale.R: code file containing the simulation example for accumulated local effects plots in the methods section of the paper
simulation_example_fi.R: code file containing the simulation example for the feature interaction H-statistics plots in the methods section of the paper
real_data_example.R: code file containing the example of an IML analysis on real data (GBSG2 dataset)
The code was produced with the following versions of R and packages:
R version 4.4.0 (2024-04-24)
Platform: aarch64-apple-darwin20
Running under: macOS 15.0.1
Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: Europe/Berlin
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] ranger_0.16.0 simsurv_1.0.0 data.table_1.15.4
[4] dplyr_1.1.4 ggbeeswarm_0.7.2 ggnewscale_0.5.0
[7] survminer_0.4.9 ggpubr_0.6.0 survAUC_1.3-0
[10] ggplot2_3.5.1 survex_1.2.0 randomForestSRC_3.3.1
[13] pec_2023.04.12 prodlim_2023.08.28 survival_3.5-8
loaded via a namespace (and not attached):
[1] gridExtra_2.3 sandwich_3.1-0 rlang_1.1.4 magrittr_2.0.3
[5] multcomp_1.4-25 polspline_1.1.25 compiler_4.4.0 vctrs_0.6.5
[9] quantreg_5.98 stringr_1.5.1 pkgconfig_2.0.3 fastmap_1.2.0
[13] backports_1.5.0 KMsurv_0.1-5 utf8_1.2.4 rmarkdown_2.27
[17] MatrixModels_0.5-3 purrr_1.0.2 xfun_0.44 jsonlite_1.8.8
[21] timereg_2.0.5 broom_1.0.6 parallel_4.4.0 data.tree_1.1.0
[25] cluster_2.1.6 R6_2.5.1 stringi_1.8.4 RColorBrewer_1.1-3
[29] parallelly_1.37.1 car_3.1-2 rpart_4.1.23 numDeriv_2016.8-1.1
[33] Rcpp_1.0.12 iterators_1.0.14 knitr_1.47 future.apply_1.11.2
[37] zoo_1.8-12 base64enc_0.1-3 Matrix_1.7-0 splines_4.4.0
[41] nnet_7.3-19 tidyselect_1.2.1 rstudioapi_0.16.0 abind_1.4-5
[45] codetools_0.2-20 listenv_0.9.1 lattice_0.22-6 tibble_3.2.1
[49] withr_3.0.0 evaluate_0.24.0 foreign_0.8-86 future_1.33.2
[53] survMisc_0.5.6 pillar_1.9.0 carData_3.0-5 DiagrammeR_1.0.11
[57] checkmate_2.3.1 foreach_1.5.2 generics_0.1.3 munsell_0.5.1
[61] scales_1.3.0 globals_0.16.3 xtable_1.8-4 glue_1.7.0
[65] rms_6.8-1 Hmisc_5.1-3 tools_4.4.0 SparseM_1.83
[69] ggsignif_0.6.4 visNetwork_2.1.2 mvtnorm_1.2-5 grid_4.4.0
[73] DALEX_2.4.3 tidyr_1.3.1 colorspace_2.1-0 nlme_3.1-164
[77] patchwork_1.2.0 beeswarm_0.4.0 htmlTable_2.4.2 vipor_0.4.7
[81] Formula_1.2-5 cli_3.6.2 km.ci_0.5-6 fansi_1.0.6
[85] lava_1.8.0 gtable_0.3.5 rstatix_0.7.2 digest_0.6.35
[89] TH.data_1.1-2 htmlwidgets_1.6.4 htmltools_0.5.8.1 lifecycle_1.0.4
[93] MASS_7.3-60.2