High-Performance Open-Source Archive
calculation_method for
surv_shap() called "treeshap" that uses the
treeshap package (#75)categorical_variables were providedmodel_survshap() function)plot.aggregated_surv_shap())model_profile(..., type = "accumulated"))model_profile_2d() function)plot(..., geom="variable") function for plotting
PDP and ALE explanations without the time dimensionflexsurv models and for Python
scikit-survival models (can be used with reticulate)model_survshap() - curves (with
functional box plot)model_diagnostics() function)"survival_quantiles"
and setting it as default (see explain())vignette("pdp") and
vignette("global-survshap"))requireNamespace()
calls (#83)model_performance_survival object - calculated metrics are
now in a $result list.calculation_method for
surv_shap() called "kernelshap" that use
kernelshap package and its implementation of improved
Kernel SHAP (set as default) (#45)"kernel" to
"exact_kernel"kernelshap
package)max_vars parameter for predict_parts explanations
(#27)max_vars to 7 for every methodset_theme_survex() (#32)predict_parts() and model_parts() explanations
in one plot (#12)surv_feature_importance.R - change auxiliary
columns to include _ in their name. Necessary changes also
done to plotting and printing functions. (#28)type argument of
model_parts() to "difference" (#33)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)model_performance() (#22)explanation_label parameter to
predict_parts() function that can overwrite explainer label
and thus, enable plotting multiple local SurvSHAP(t) explanations. (#47)gridExtra to patchwork (#7)mlr3proba (#10)mlr3proba with
survexingredients from imports to suggestssurvex package is now publicmodel_parts, model_profile,
predict_parts, predict_profile explanations
implementedsurvival, ranger,
randomForestSRC, censored and
mlr3proba packages.
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