Changelog

Source: NEWS.md

survex 1.2.02023-10-24

  • added new calculation_method for surv_shap() called "treeshap" that uses the treeshap package (#75)
  • enable to calculate SurvSHAP(t) explanations based on subsample of the explainer’s data
  • changed default kernel width in SurvLIME from sqrt(p * 0.75) to sqrt(p) * 0.75
  • fixed error in SurvLIME when non-factor categorical_variables were provided

survex 1.1.32023-09-06

  • fixed not being able to plot or print SurvLIME results for the cph model sometimes. (#72)
  • added global explanations via the SurvSHAP(t) method (see model_survshap() function)
  • added plots for global SurvSHAP(t) explanations (see plot.aggregated_surv_shap())
  • added Accumulated Local Effects (ALE) explanations (see model_profile(..., type = "accumulated"))
  • added 2-dimensional PDP and ALE plots (see model_profile_2d() function)
  • added plot(..., geom="variable") function for plotting PDP and ALE explanations without the time dimension
  • new explainers: for flexsurv models and for Python scikit-survival models (can be used with reticulate)
  • new plot type for model_survshap() - curves (with functional box plot)
  • added diagnostic explanations - residual analysis (see model_diagnostics() function)
  • added new times generation method "survival_quantiles" and setting it as default (see explain())
  • made improvements on the vignettes for the package (see vignette("pdp") and vignette("global-survshap"))
  • increased the test coverage of the package
  • reduced the number of expensive requireNamespace() calls (#83)

survex 1.0.02023-03-20

  • breaking change: refactored the structure of model_performance_survival object - calculated metrics are now in a $result list.
  • added new calculation_method for surv_shap() called "kernelshap" that use kernelshap package and its implementation of improved Kernel SHAP (set as default) (#45)
  • rename old method "kernel" to "exact_kernel"
  • added new import (kernelshap package)
  • fixed invalid color palette order in plot feature importance
  • fixed predict_parts survshap running out of memory with more than 16 variables (#25)
  • added max_vars parameter for predict_parts explanations (#27)
  • set max_vars to 7 for every method
  • refactored survshap code (#29, #30, #43)
  • fixed survshap error when target columns named different than time and status (#44)
  • fixed survlime error when all variables are categorical (#46)
  • fixed subtitles in feature importance plots (#11)
  • added the possibility to set themes with set_theme_survex() (#32)
  • added the possibility of plotting multiple predict_parts() and model_parts() explanations in one plot (#12)
  • fixed the x axis of plots (it now starts from 0) (#37)
  • added geom_rug() to all time-dependent plots, marking event and censoring times (#35)
  • refactored surv_feature_importance.R - change auxiliary columns to include _ in their name. Necessary changes also done to plotting and printing functions. (#28)
  • changed default type argument of model_parts() to "difference" (#33)
  • refactored integration of metrics (#31)
  • changed behaviour of categorical_variables argument in model_parts() and predict_parts(). If it contains variable names not present in the variables argument, they will be added at the end. (#39)
  • added ROC AUC calculation and plotting for selected timepoints in model_performance() (#22)
  • added explanation_label parameter to predict_parts() function that can overwrite explainer label and thus, enable plotting multiple local SurvSHAP(t) explanations. (#47)
  • improved the printing of the explainer (#36)
  • reduced the default number of time points for evaluation when creating the explainer to 50

survex 0.2.22022-11-30

  • improved and unified API documentation (#2)
  • added references to used methods (#5)
  • changed the package used to draw complex plots from gridExtra to patchwork (#7)
  • fixed subtitles in plots (#11)
  • fixed calculating of ROC curves for classification problems (#17)
  • added wrapper function for measures provided by mlr3proba (#10)
  • created vignette showing how to use mlr3proba with survex
  • fixed incompatibility with new ggplot2 version 3.4
  • added function for creating integrated versions of time-dependent metrics (#9)
  • move ingredients from imports to suggests

survex 0.1.12022-09-05

  • The survex package is now public
  • model_parts, model_profile, predict_parts, predict_profile explanations implemented
  • C/D AUC, Brier score and (Harrell’s) concordance index performance measures implemented
  • Explain methods for survival, ranger, randomForestSRC, censored and mlr3proba packages.