This function plots objects of class "predict_parts_survival" - local explanations for survival models created using the predict_parts() function.
## S3 method for class 'predict_parts_survival'plot(x,...)
Arguments
x: an object of class "predict_parts_survival" to be plotted
...: additional parameters passed to the plot.surv_shap or plot.surv_lime functions
Returns
An object of the class ggplot.
Plot options
plot.surv_shap
x - an object of class "surv_shap" to be plotted
... - additional objects of class surv_shap to be plotted together
title - character, title of the plot
subtitle - character, subtitle of the plot, 'default' automatically generates "created for XXX, YYY models", where XXX and YYY are the explainer labels
max_vars - maximum number of variables to be plotted (least important variables are ignored)
colors - character vector containing the colors to be used for plotting variables (containing either hex codes "#FF69B4", or names "blue")
rug - character, one of "all", "events", "censors", "none" or NULL. Which times to mark on the x axis in geom_rug().
rug_colors - character vector containing two colors (containing either hex codes "#FF69B4", or names "blue"). The first color (red by default) will be used to mark event times, whereas the second (grey by default) will be used to mark censor times.
plot.surv_lime
x - an object of class "surv_lime" to be plotted
type - character, either "coefficients" or "local_importance", selects the type of plot
show_survival_function - logical, if the survival function of the explanations should be plotted next to the barplot
... - other parameters currently ignored
title - character, title of the plot
subtitle - character, subtitle of the plot, 'default' automatically generates "created for XXX, YYY models", where XXX and YYY are the explainer labels
max_vars - maximum number of variables to be plotted (least important variables are ignored)
colors - character vector containing the colors to be used for plotting variables (containing either hex codes "#FF69B4", or names "blue")
Examples
library(survival)library(survex)model <- randomForestSRC::rfsrc(Surv(time, status)~ ., data = veteran)exp <- explain(model)p_parts_shap <- predict_parts(exp, veteran[1,-c(3,4)], type ="survshap")plot(p_parts_shap)p_parts_lime <- predict_parts(exp, veteran[1,-c(3,4)], type ="survlime")plot(p_parts_lime)
See Also
Other functions for plotting 'predict_parts_survival' objects: plot.surv_lime(), plot.surv_shap()