- 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 explainerâ€™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

- 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)

*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

- 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

- The
`survex`

package is now public `model_parts`

,`model_profile`

,`predict_parts`

,`predict_profile`

explanations implemented- C/D AUC, Brier score and (Harrellâ€™s) concordance index performance measures implemented
- Explain methods for
`survival`

,`ranger`

,`randomForestSRC`

,`censored`

and`mlr3proba`

packages.